{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Speech Emotion Recognition.ipynb",
"provenance": [],
"collapsed_sections": [
"tGcBNE9w2W19",
"7N_2JOi42clH",
"FLk0Nenl2p_1",
"Qrgdzbe42wYG"
]
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"<div style=\"border-radius:10px;\n",
" border:#0b0265 solid;\n",
" background-color:#DDF6A0;\n",
" font-size:110%;\n",
" letter-spacing:0.5px;\n",
" text-align: center\">\n",
"\n",
"<center><h1 style=\"padding: 25px 0px; color:#0b0265; font-weight: bold; font-family: Cursive\">\n",
"Speech Emotion Recognition 😁😍🤮😔😨😡</h1></center> \n",
"\n",
"</div>"
],
"metadata": {
"id": "qbFugeNH3B6m"
}
},
{
"cell_type": "markdown",
"source": [
"<p align=\"center\">\n",
" <img width=\"1000\" height=\"400\" src=\"https://miro.medium.com/max/1400/1*-5u1LG7fKmIwl2pSuJeSuA.jpeg\">\n",
"</p>"
],
"metadata": {
"id": "lyyg_4UWpWwt"
}
},
{
"cell_type": "markdown",
"source": [
"# <a name='Import_Libraries_and_Data'></a>\n",
"\n",
"<div style=\"border-radius:10px;\n",
" background-color:#ffffff;\n",
" border-style: solid;\n",
" border-color: #0b0265;\n",
" letter-spacing:0.5px;\">\n",
"\n",
"<center><h3 style=\"padding: 5px 0px; color:#0b0265; font-weight: bold; font-family: Cursive\">\n",
"1. Import Libraries and Data</h3></center>\n",
"</div>\n",
"\n",
"<a href=\"#toc\" class=\"btn btn-primary btn-sm\" role=\"button\" aria-pressed=\"true\" style=\"color:white\" data-toggle=\"popover\">Back to Table of Contents</a>"
],
"metadata": {
"id": "tGcBNE9w2W19"
}
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "_mngszrwnvB4",
"outputId": "94c9cab4-fcb6-4857-c238-8cc61cf4b835"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
"Requirement already satisfied: librosa in /usr/local/lib/python3.7/dist-packages (0.8.1)\n",
"Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (1.21.6)\n",
"Requirement already satisfied: joblib>=0.14 in /usr/local/lib/python3.7/dist-packages (from librosa) (1.1.0)\n",
"Requirement already satisfied: decorator>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (4.4.2)\n",
"Requirement already satisfied: resampy>=0.2.2 in /usr/local/lib/python3.7/dist-packages (from librosa) (0.3.1)\n",
"Requirement already satisfied: pooch>=1.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (1.6.0)\n",
"Requirement already satisfied: numba>=0.43.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (0.51.2)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (21.3)\n",
"Requirement already satisfied: scipy>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (1.7.3)\n",
"Requirement already satisfied: audioread>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (2.1.9)\n",
"Requirement already satisfied: scikit-learn!=0.19.0,>=0.14.0 in /usr/local/lib/python3.7/dist-packages (from librosa) (1.0.2)\n",
"Requirement already satisfied: soundfile>=0.10.2 in /usr/local/lib/python3.7/dist-packages (from librosa) (0.10.3.post1)\n",
"Requirement already satisfied: llvmlite<0.35,>=0.34.0.dev0 in /usr/local/lib/python3.7/dist-packages (from numba>=0.43.0->librosa) (0.34.0)\n",
"Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from numba>=0.43.0->librosa) (57.4.0)\n",
"Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=20.0->librosa) (3.0.9)\n",
"Requirement already satisfied: appdirs>=1.3.0 in /usr/local/lib/python3.7/dist-packages (from pooch>=1.0->librosa) (1.4.4)\n",
"Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.7/dist-packages (from pooch>=1.0->librosa) (2.23.0)\n",
"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa) (1.24.3)\n",
"Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa) (3.0.4)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa) (2022.6.15)\n",
"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa) (2.10)\n",
"Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn!=0.19.0,>=0.14.0->librosa) (3.1.0)\n",
"Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.7/dist-packages (from soundfile>=0.10.2->librosa) (1.15.1)\n",
"Requirement already satisfied: pycparser in /usr/local/lib/python3.7/dist-packages (from cffi>=1.0->soundfile>=0.10.2->librosa) (2.21)\n"
]
}
],
"source": [
"!pip install librosa"
]
},
{
"cell_type": "code",
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import os\n",
"import glob\n",
"from pathlib import Path\n",
"\n",
"import librosa\n",
"import librosa.display\n",
"import IPython\n",
"from IPython.display import Audio\n",
"from scipy.io.wavfile import read, write\n",
"\n",
"from sklearn.preprocessing import StandardScaler, OneHotEncoder\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.metrics import confusion_matrix, classification_report\n",
"import sklearn\n",
"\n",
"import tensorflow as tf\n",
"from tensorflow.keras.utils import plot_model\n",
"from keras.callbacks import ModelCheckpoint\n",
"from tensorflow.keras.models import load_model, save_model"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "AFGhdKODoctt",
"outputId": "8d295b8a-1be6-4179-c25f-b03552ef38bb"
},
"execution_count": 3,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.7/dist-packages/resampy/interpn.py:114: NumbaWarning: The TBB threading layer requires TBB version 2019.5 or later i.e., TBB_INTERFACE_VERSION >= 11005. Found TBB_INTERFACE_VERSION = 9107. The TBB threading layer is disabled.\n",
" _resample_loop_p(x, t_out, interp_win, interp_delta, num_table, scale, y)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"! pip install kaggle\n",
"! mkdir ~/.kaggle\n",
"! cp kaggle.json ~/.kaggle/\n",
"! chmod 600 ~/.kaggle/kaggle.json\n",
"! kaggle datasets download ejlok1/toronto-emotional-speech-set-tess\n",
"! unzip /content/toronto-emotional-speech-set-tess.zip"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"collapsed": true,
"id": "kjajWMUgpigM",
"outputId": "7724c73a-2998-49ea-968b-f1997aabcdb2"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_back_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_bar_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_base_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_bath_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_bean_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_beg_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_bite_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_boat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_bone_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_book_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_bought_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_burn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_cab_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_calm_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_came_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_cause_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_chain_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_chair_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_chalk_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_chat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_check_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_cheek_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_chief_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_choice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_cool_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_dab_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_date_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_dead_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_death_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_deep_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_dime_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_dip_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_ditch_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_dodge_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_dog_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_doll_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_door_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_fail_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_fall_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_far_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_fat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_fit_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_five_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_food_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_gap_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_gas_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_gaze_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_germ_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_get_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_gin_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_goal_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_good_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_goose_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_gun_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_half_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hall_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hash_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hate_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_have_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_haze_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hire_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hit_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hole_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_home_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hurl_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_hush_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_jail_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_jar_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_join_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_judge_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_jug_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_juice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_keen_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_keep_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_keg_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_kick_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_kill_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_king_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_kite_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_knock_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_late_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_laud_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_lean_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_learn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_lease_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_lid_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_life_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_limb_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_live_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_loaf_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_long_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_lore_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_lose_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_lot_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_love_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_luck_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_make_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_match_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_merge_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mess_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_met_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mill_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mob_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mode_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mood_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_moon_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mop_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_mouse_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_nag_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_name_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_near_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_neat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_nice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_note_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_numb_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pad_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_page_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pain_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pass_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pearl_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_peg_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_perch_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_phone_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pick_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pike_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pole_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_pool_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_puff_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rag_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_raid_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rain_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_raise_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_reach_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_read_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_red_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_ring_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_ripe_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_road_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_room_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rose_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rot_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rough_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_rush_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_said_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_sail_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_search_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_seize_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_sell_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_shack_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_shall_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_shawl_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_sheep_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_shirt_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_should_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_shout_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_size_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_soap_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_soup_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_sour_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_south_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_sub_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_such_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_sure_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_take_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_talk_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_tape_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_team_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_tell_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_thin_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_third_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_thought_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_thumb_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_time_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_tip_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_tire_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_ton_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_tool_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_tough_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_turn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_vine_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_voice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_void_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_vote_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_wag_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_walk_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_wash_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_week_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_wheat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_when_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_which_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_whip_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_white_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_wife_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_wire_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_witch_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_yearn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_yes_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_young_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_angry/OAF_youth_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_back_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_bar_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_base_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_bath_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_bean_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_beg_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_bite_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_boat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_bone_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_book_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_bought_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_burn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_cab_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_calm_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_came_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_cause_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_chain_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_chair_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_chalk_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_chat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_check_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_cheek_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_chief_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_choice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_cool_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_dab_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_date_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_dead_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_death_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_deep_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_dime_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_dip_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_ditch_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_dodge_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_dog_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_doll_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_door_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_fail_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_fall_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_far_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_fat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_fit_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_five_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_food_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_gap_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_gas_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_gaze_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_germ_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_get_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_gin_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_goal_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_good_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_goose_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_gun_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_half_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hall_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hash_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hate_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_have_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_haze_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hire_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hit_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hole_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_home_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hurl_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_hush_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_jail_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_jar_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_join_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_judge_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_jug_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_juice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_keen_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_keep_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_keg_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_kick_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_kill_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_king_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_kite_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_knock_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_late_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_laud_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_lean_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_learn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_lease_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_lid_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_life_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_limb_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_live_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_loaf_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_long_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_lore_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_lose_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_lot_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_love_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_luck_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_make_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_match_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_merge_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mess_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_met_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mill_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mob_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mode_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mood_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_moon_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mop_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_mouse_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_nag_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_name_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_near_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_neat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_nice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_note_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_numb_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pad_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_page_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pain_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pass_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pearl_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_peg_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_perch_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_phone_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pick_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pike_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pole_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_pool_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_puff_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rag_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_raid_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rain_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_raise_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_reach_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_read_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_red_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_ring_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_ripe_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_road_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_room_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rose_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rot_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rough_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_rush_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_said_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_sail_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_search_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_seize_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_sell_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_shack_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_shall_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_shawl_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_sheep_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_shirt_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_should_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_shout_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_size_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_soap_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_soup_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_sour_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_south_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_sub_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_such_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_sure_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_take_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_talk_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_tape_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_team_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_tell_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_thin_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_third_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_thought_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_thumb_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_time_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_tip_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_tire_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_ton_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_tool_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_tough_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_turn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_vine_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_voice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_void_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_vote_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_wag_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_walk_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_wash_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_week_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_wheat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_when_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_which_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_whip_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_white_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_wife_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_wire_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_witch_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_yearn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_yes_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_young_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_disgust/OAF_youth_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_back_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_bar_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_base_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_bath_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_bean_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_beg_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_bite_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_boat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_bone_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_book_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_bought_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_burn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_cab_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_calm_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_came_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_cause_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_chain_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_chair_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_chalk_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_chat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_check_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_cheek_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_chief_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_choice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_cool_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_dab_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_date_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_dead_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_death_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_deep_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_dime_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_dip_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_ditch_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_dodge_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_dog_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_doll_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_door_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_fail_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_fall_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_far_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_fat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_fit_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_five_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_food_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_gap_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_gas_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_gaze_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_germ_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_get_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_gin_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_goal_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_good_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_goose_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_gun_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_half_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hall_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hash_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hate_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_have_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_haze_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hire_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hit_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hole_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_home_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hurl_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_hush_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_jail_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_jar_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_join_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_judge_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_jug_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_juice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_keen_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_keep_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_keg_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_kick_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_kill_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_king_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_kite_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_knock_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_late_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_laud_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_lean_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_learn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_lease_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_lid_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_life_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_limb_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_live_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_loaf_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_long_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_lore_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_lose_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_lot_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_love_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_luck_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_make_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_match_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_merge_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mess_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_met_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mill_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mob_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mode_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mood_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_moon_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mop_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_mouse_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_nag_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_name_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_near_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_neat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_nice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_note_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_numb_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pad_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_page_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pain_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pass_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pearl_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_peg_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_perch_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_phone_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pick_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pike_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pole_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_pool_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_puff_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rag_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_raid_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rain_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_raise_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_reach_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_read_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_red_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_ring_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_ripe_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_road_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_room_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rose_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rot_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rough_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_rush_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_said_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_sail_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_search_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_seize_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_sell_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_shack_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_shall_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_shawl_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_sheep_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_shirt_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_should_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_shout_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_size_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_soap_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_soup_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_sour_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_south_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_sub_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_such_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_sure_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_take_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_talk_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_tape_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_team_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_tell_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_thin_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_third_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_thought_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_thumb_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_time_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_tip_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_tire_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_ton_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_tool_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_tough_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_turn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_vine_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_voice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_void_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_vote_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_wag_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_walk_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_wash_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_week_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_wheat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_when_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_which_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_whip_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_white_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_wife_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_wire_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_witch_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_yearn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_yes_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_young_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_happy/OAF_youth_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_back_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_bar_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_base_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_bath_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_bean_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_beg_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_boat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_bone_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_book_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_bought_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_burn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_cab_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_calm_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_came_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_cause_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_chain_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_chair_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_chalk_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_chat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_check_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_cheek_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_chief_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_choice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_cool_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_dab_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_date_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_dead_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_death_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_deep_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_dime_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_dip_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_ditch_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_dodge_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_dog_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_doll_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_door_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_fail_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_fall_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_far_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_fat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_fit_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_five_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_food_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_gap_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_gas_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_gaze_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_germ_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_get_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_gin_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_goal_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_good_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_goose_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_gun_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_half_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hall_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hash_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hate_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_have_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_haze_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hire_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hit_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hole_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_home_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hurl_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_hush_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_jail_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_jar_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_join_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_judge_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_jug_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_juice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_keen_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_keep_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_keg_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_kick_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_kill_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_king_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_kite_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_knock_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_late_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_laud_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_lean_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_learn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_lease_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_lid_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_life_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_limb_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_live_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_loaf_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_long_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_lore_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_lose_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_lot_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_love_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_luck_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_make_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_match_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_merge_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mess_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_met_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mill_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mob_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mode_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mood_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_moon_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mop_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_mouse_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_nag_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_name_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_near_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_neat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_nice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_note_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_numb_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pad_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_page_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pain_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pass_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pearl_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_peg_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_perch_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_phone_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pick_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pike_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pole_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_pool_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_puff_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rag_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_raid_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rain_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_raise_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_reach_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_read_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_red_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_ring_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_ripe_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_road_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_room_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rose_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rot_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rough_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_rush_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_said_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_sail_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_search_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_seize_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_sell_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_shack_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_shall_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_shawl_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_sheep_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_shirt_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_should_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_shout_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_size_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_soap_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_soup_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_sour_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_south_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_sub_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_such_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_sure_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_take_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_talk_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_tape_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_team_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_tell_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_thin_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_third_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_thought_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_thumb_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_time_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_tip_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_tire_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_ton_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_tool_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_tough_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_turn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_vine_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_voice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_void_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_vote_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_wag_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_walk_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_wash_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_week_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_wheat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_when_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_which_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_whip_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_white_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_wife_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_wire_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_witch_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_yearn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_yes_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_young_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OAF_youth_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/OAF_neutral/OA_bite_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_back_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_bar_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_base_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_bath_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_bean_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_beg_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_bite_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_boat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_bone_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_book_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_bought_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_burn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_cab_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_calm_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_came_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_cause_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_chain_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_chair_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_chalk_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_chat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_check_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_cheek_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_chief_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_choice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_cool_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_dab_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_date_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_dead_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_death_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_deep_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_dime_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_dip_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_ditch_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_dodge_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_dog_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_doll_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_door_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_fail_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_fall_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_far_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_fat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_fit_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_five_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_food_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_gap_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_gas_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_gaze_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_germ_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_get_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_gin_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_goal_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_good_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_goose_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_gun_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_half_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hall_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hash_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hate_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_have_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_haze_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hire_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hit_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hole_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_home_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hurl_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_hush_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_jail_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_jar_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_join_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_judge_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_jug_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_juice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_keen_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_keep_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_keg_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_kick_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_kill_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_king_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_kite_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_knock_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_late_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_laud_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_lean_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_learn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_lease_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_lid_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_life_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_limb_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_live_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_loaf_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_long_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_lore_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_lose_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_lot_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_love_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_luck_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_make_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_match_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_merge_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mess_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_met_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mill_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mob_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mode_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mood_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_moon_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mop_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_mouse_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_nag_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_name_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_near_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_neat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_nice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_note_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_numb_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pad_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_page_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pain_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pass_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pearl_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_peg_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_perch_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_phone_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pick_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pike_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pole_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_pool_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_puff_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rag_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_raid_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rain_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_raise_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_reach_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_read_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_red_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_ring_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_ripe_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_road_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_room_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rose_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rot_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rough_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_rush_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_said_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_sail_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_search_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_seize_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_sell_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_shack_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_shall_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_shawl_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_sheep_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_shirt_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_should_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_shout_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_size_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_soap_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_soup_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_sour_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_south_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_sub_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_such_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_sure_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_take_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_talk_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_tape_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_team_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_tell_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_thin_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_third_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_thought_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_thumb_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_time_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_tip_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_tire_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_ton_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_tool_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_tough_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_turn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_vine_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_voice_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_void_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_vote_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_wag_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_walk_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_wash_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_week_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_wheat_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_when_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_which_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_whip_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_white_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_wife_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_wire_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_witch_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_yearn_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_yes_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_young_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_angry/YAF_youth_angry.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_back_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_bar_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_base_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_bath_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_bean_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_beg_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_bite_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_boat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_bone_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_book_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_bought_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_burn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_cab_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_calm_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_came_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_cause_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_chain_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_chair_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_chalk_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_chat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_check_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_cheek_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_chief_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_choice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_cool_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_dab_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_date_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_dead_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_death_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_deep_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_dime_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_dip_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_ditch_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_dodge_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_dog_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_doll_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_door_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_fail_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_fall_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_far_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_fat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_fit_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_five_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_food_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_gap_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_gas_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_gaze_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_germ_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_get_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_gin_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_goal_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_good_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_goose_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_gun_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_half_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hall_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hash_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hate_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_have_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_haze_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hire_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hit_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hole_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_home_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hurl_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_hush_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_jail_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_jar_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_join_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_judge_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_jug_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_juice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_keen_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_keep_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_keg_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_kick_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_kill_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_king_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_kite_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_knock_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_late_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_laud_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_lean_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_learn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_lease_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_lid_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_life_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_limb_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_live_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_loaf_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_long_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_lore_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_lose_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_lot_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_love_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_luck_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_make_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_match_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_merge_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mess_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_met_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mill_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mob_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mode_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mood_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_moon_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mop_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_mouse_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_nag_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_name_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_near_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_neat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_nice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_note_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_numb_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pad_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_page_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pain_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pass_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pearl_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_peg_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_perch_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_phone_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pick_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pike_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pole_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_pool_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_puff_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rag_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_raid_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rain_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_raise_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_reach_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_read_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_red_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_ring_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_ripe_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_road_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_room_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rose_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rot_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rough_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_rush_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_said_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_sail_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_search_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_seize_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_sell_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_shack_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_shall_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_shawl_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_sheep_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_shirt_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_should_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_shout_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_size_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_soap_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_soup_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_sour_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_south_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_sub_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_such_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_sure_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_take_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_talk_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_tape_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_team_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_tell_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_thin_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_third_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_thought_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_thumb_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_time_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_tip_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_tire_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_ton_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_tool_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_tough_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_turn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_vine_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_voice_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_void_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_vote_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_wag_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_walk_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_wash_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_week_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_wheat_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_when_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_which_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_whip_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_white_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_wife_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_wire_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_witch_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_yearn_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_yes_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_young_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_disgust/YAF_youth_disgust.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_back_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_bar_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_base_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_bath_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_bean_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_beg_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_bite_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_boat_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_bone_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_book_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_bought_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_burn_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_cab_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_calm_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_came_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_cause_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_chain_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_chair_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_chalk_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_chat_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_check_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_cheek_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_chief_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_choice_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_cool_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_dab_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_date_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_dead_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_death_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_deep_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_dime_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_dip_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_ditch_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_dodge_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_dog_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_doll_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_door_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_fail_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_fall_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_far_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_fat_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_fit_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_five_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_food_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_gap_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_gas_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_gaze_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_germ_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_get_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_gin_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_goal_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_good_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_goose_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_gun_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_half_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hall_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hash_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hate_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_have_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_haze_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hire_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hit_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hole_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_home_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hurl_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_hush_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_jail_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_jar_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_join_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_judge_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_jug_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_juice_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_keen_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_keep_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_keg_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_kick_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_kill_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_king_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_kite_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_knock_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_late_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_laud_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_lean_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_learn_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_lease_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_lid_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_life_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_limb_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_live_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_loaf_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_long_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_lore_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_lose_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_lot_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_love_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_luck_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_make_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_match_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_merge_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mess_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_met_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mill_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mob_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mode_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mood_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_moon_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mop_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_mouse_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_nag_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_name_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_near_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_neat_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_nice_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_note_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_numb_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pad_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_page_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pain_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pass_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pearl_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_peg_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_perch_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_phone_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pick_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pike_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pole_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_pool_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_puff_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rag_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_raid_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rain_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_raise_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rat_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_reach_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_read_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_red_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_ring_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_ripe_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_road_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_room_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rose_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rot_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rough_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_rush_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_said_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_sail_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_search_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_seize_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_sell_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_shack_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_shall_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_shawl_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_sheep_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_shirt_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_should_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_shout_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_size_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_soap_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_soup_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_sour_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_south_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_sub_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_such_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_sure_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_take_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_talk_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_tape_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_team_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_tell_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_thin_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_third_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_thought_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_thumb_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_time_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_tip_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_tire_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_ton_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_tool_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_tough_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_turn_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_vine_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_voice_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_void_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_vote_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_wag_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_walk_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_wash_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_week_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_wheat_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_when_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_which_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_whip_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_white_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_wife_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_wire_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_witch_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_yearn_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_yes_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_young_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_fear/YAF_youth_fear.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_back_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_bar_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_base_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_bath_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_bean_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_beg_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_bite_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_boat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_bone_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_book_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_bought_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_burn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_cab_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_calm_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_came_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_cause_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_chain_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_chair_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_chalk_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_chat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_check_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_cheek_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_chief_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_choice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_cool_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_dab_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_date_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_dead_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_death_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_deep_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_dime_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_dip_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_ditch_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_dodge_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_dog_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_doll_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_door_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_fail_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_fall_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_far_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_fat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_fit_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_five_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_food_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_gap_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_gas_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_gaze_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_germ_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_get_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_gin_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_goal_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_good_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_goose_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_gun_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_half_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hall_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hash_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hate_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_have_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_haze_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hire_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hit_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hole_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_home_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hurl_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_hush_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_jail_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_jar_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_join_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_judge_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_jug_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_juice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_keen_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_keep_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_keg_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_kick_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_kill_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_king_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_kite_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_knock_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_late_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_laud_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_lean_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_learn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_lease_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_lid_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_life_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_limb_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_live_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_loaf_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_long_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_lore_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_lose_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_lot_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_love_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_luck_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_make_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_match_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_merge_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mess_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_met_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mill_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mob_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mode_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mood_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_moon_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mop_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_mouse_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_nag_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_name_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_near_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_neat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_nice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_note_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_numb_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pad_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_page_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pain_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pass_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pearl_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_peg_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_perch_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_phone_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pick_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pike_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pole_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_pool_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_puff_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rag_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_raid_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rain_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_raise_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_reach_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_read_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_red_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_ring_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_ripe_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_road_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_room_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rose_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rot_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rough_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_rush_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_said_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_sail_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_search_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_seize_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_sell_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_shack_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_shall_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_shawl_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_sheep_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_shirt_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_should_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_shout_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_size_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_soap_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_soup_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_sour_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_south_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_sub_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_such_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_sure_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_take_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_talk_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_tape_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_team_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_tell_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_thin_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_third_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_thought_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_thumb_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_time_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_tip_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_tire_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_ton_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_tool_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_tough_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_turn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_vine_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_voice_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_void_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_vote_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_wag_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_walk_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_wash_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_week_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_wheat_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_when_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_which_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_whip_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_white_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_wife_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_wire_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_witch_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_yearn_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_yes_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_young_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_happy/YAF_youth_happy.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_back_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_bar_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_base_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_bath_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_bean_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_beg_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_bite_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_boat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_bone_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_book_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_bought_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_burn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_cab_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_calm_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_came_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_cause_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_chain_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_chair_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_chalk_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_chat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_check_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_cheek_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_chief_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_choice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_cool_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_dab_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_date_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_dead_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_death_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_deep_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_dime_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_dip_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_ditch_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_dodge_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_dog_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_doll_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_door_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_fail_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_fall_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_far_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_fat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_fit_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_five_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_food_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_gap_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_gas_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_gaze_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_germ_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_get_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_gin_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_goal_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_good_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_goose_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_gun_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_half_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hall_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hash_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hate_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_have_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_haze_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hire_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hit_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hole_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_home_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hurl_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_hush_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_jail_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_jar_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_join_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_judge_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_jug_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_juice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_keen_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_keep_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_keg_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_kick_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_kill_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_king_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_kite_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_knock_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_late_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_laud_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_lean_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_learn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_lease_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_lid_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_life_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_limb_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_live_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_loaf_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_long_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_lore_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_lose_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_lot_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_love_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_luck_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_make_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_match_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_merge_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mess_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_met_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mill_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mob_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mode_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mood_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_moon_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mop_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_mouse_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_nag_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_name_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_near_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_neat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_nice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_note_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_numb_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pad_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_page_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pain_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pass_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pearl_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_peg_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_perch_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_phone_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pick_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pike_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pole_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_pool_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_puff_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rag_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_raid_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rain_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_raise_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_reach_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_read_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_red_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_ring_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_ripe_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_road_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_room_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rose_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rot_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rough_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_rush_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_said_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_sail_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_search_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_seize_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_sell_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_shack_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_shall_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_shawl_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_sheep_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_shirt_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_should_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_shout_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_size_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_soap_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_soup_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_sour_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_south_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_sub_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_such_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_sure_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_take_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_talk_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_tape_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_team_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_tell_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_thin_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_third_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_thought_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_thumb_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_time_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_tip_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_tire_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_ton_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_tool_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_tough_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_turn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_vine_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_voice_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_void_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_vote_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_wag_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_walk_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_wash_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_week_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_wheat_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_when_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_which_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_whip_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_white_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_wife_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_wire_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_witch_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_yearn_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_yes_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_young_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_neutral/YAF_youth_neutral.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_back_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bar_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_base_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bath_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bean_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_beg_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bite_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_boat_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bone_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_book_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bought_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_burn_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cab_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_calm_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_came_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cause_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chain_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chair_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chalk_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chat_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_check_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cheek_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chief_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_choice_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cool_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_dab_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_date_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_dead_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_death_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_deep_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_dime_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_dip_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ditch_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_dodge_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_dog_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_doll_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_door_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_fail_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_fall_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_far_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_fat_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_fit_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_five_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_food_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_gap_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_gas_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_gaze_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_germ_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_get_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_gin_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_goal_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_good_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_goose_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_gun_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_half_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hall_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hash_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hate_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_have_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_haze_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hire_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hit_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hole_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_home_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hurl_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_hush_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_jail_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_jar_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_join_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_judge_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_jug_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_juice_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_keen_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_keep_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_keg_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_kick_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_kill_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_king_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_kite_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_knock_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_late_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_laud_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lean_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_learn_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lease_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lid_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_life_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_limb_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_live_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_loaf_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_long_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lore_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lose_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lot_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_love_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_luck_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_make_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_match_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_merge_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mess_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_met_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mill_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mob_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mode_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mood_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_moon_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mop_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mouse_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_nag_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_name_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_near_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_neat_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_nice_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_note_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_numb_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pad_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_page_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pain_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pass_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pearl_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_peg_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_perch_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_phone_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pick_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pike_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pole_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pool_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_puff_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rag_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_raid_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rain_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_raise_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rat_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_reach_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_read_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_red_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ring_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ripe_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_road_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_room_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rose_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rot_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rough_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rush_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_said_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sail_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_search_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_seize_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sell_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shack_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shall_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shawl_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sheep_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shirt_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_should_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shout_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_size_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_soap_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_soup_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sour_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_south_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sub_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_such_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sure_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_take_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_talk_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tape_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_team_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tell_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_thin_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_third_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_thought_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_thumb_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_time_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tip_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tire_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ton_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tool_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tough_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_turn_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_vine_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_voice_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_void_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_vote_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wag_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_walk_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wash_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_week_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wheat_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_when_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_which_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_whip_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_white_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wife_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wire_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_witch_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_yearn_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_yes_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_young_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_youth_ps.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_back_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_bar_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_base_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_bath_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_bean_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_beg_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_bite_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_boat_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_bone_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_book_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_bought_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_burn_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_cab_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_calm_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_came_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_cause_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_chain_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_chair_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_chalk_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_chat_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_check_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_cheek_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_chief_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_choice_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_cool_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_dab_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_date_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_dead_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_death_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_deep_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_dime_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_dip_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_ditch_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_dodge_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_dog_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_doll_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_door_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_fail_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_fall_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_far_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_fat_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_fit_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_five_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_food_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_gap_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_gas_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_gaze_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_germ_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_get_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_gin_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_goal_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_good_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_goose_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_gun_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_half_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hall_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hash_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hate_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_have_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_haze_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hire_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hit_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hole_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_home_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hurl_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_hush_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_jail_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_jar_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_join_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_judge_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_jug_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_juice_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_keen_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_keep_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_keg_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_kick_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_kill_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_king_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_kite_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_knock_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_late_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_laud_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_lean_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_learn_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_lease_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_lid_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_life_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_limb_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_live_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_loaf_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_long_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_lore_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_lose_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_lot_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_love_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_luck_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_make_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_match_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_merge_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mess_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_met_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mill_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mob_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mode_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mood_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_moon_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mop_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_mouse_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_nag_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_name_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_near_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_neat_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_nice_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_note_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_numb_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pad_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_page_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pain_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pass_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pearl_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_peg_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_perch_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_phone_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pick_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pike_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pole_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_pool_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_puff_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rag_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_raid_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rain_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_raise_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rat_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_reach_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_read_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_red_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_ring_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_ripe_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_road_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_room_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rose_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rot_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rough_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_rush_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_said_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_sail_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_search_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_seize_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_sell_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_shack_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_shall_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_shawl_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_sheep_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_shirt_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_should_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_shout_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_size_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_soap_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_soup_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_sour_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_south_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_sub_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_such_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_sure_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_take_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_talk_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_tape_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_team_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_tell_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_thin_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_third_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_thought_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_thumb_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_time_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_tip_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_tire_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_ton_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_tool_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_tough_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_turn_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_vine_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_voice_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_void_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_vote_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_wag_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_walk_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_wash_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_week_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_wheat_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_when_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_which_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_whip_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_white_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_wife_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_wire_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_witch_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_yearn_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_yes_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_young_sad.wav \n",
" inflating: TESS Toronto emotional speech set data/YAF_sad/YAF_youth_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_back_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_bar_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_base_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_bath_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_bean_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_beg_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_bite_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_boat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_bone_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_book_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_bought_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_burn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_cab_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_calm_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_came_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_cause_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_chain_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_chair_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_chalk_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_chat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_check_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_cheek_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_chief_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_choice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_cool_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_dab_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_date_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_dead_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_death_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_deep_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_dime_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_dip_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_ditch_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_dodge_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_dog_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_doll_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_door_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_fail_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_fall_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_far_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_fat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_fit_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_five_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_food_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_gap_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_gas_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_gaze_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_germ_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_get_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_gin_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_goal_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_good_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_goose_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_gun_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_half_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hall_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hash_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hate_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_have_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_haze_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hire_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hit_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hole_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_home_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hurl_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_hush_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_jail_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_jar_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_join_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_judge_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_jug_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_juice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_keen_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_keep_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_keg_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_kick_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_kill_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_king_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_kite_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_knock_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_late_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_laud_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_lean_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_learn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_lease_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_lid_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_life_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_limb_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_live_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_loaf_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_long_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_lore_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_lose_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_lot_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_love_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_luck_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_make_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_match_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_merge_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mess_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_met_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mill_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mob_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mode_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mood_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_moon_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mop_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_mouse_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_nag_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_name_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_near_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_neat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_nice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_note_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_numb_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pad_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_page_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pain_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pass_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pearl_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_peg_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_perch_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_phone_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pick_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pike_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pole_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_pool_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_puff_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rag_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_raid_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rain_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_raise_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_reach_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_read_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_red_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_ring_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_ripe_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_road_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_room_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rose_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rot_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rough_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_rush_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_said_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_sail_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_search_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_seize_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_sell_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_shack_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_shall_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_shawl_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_sheep_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_shirt_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_should_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_shout_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_size_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_soap_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_soup_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_sour_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_south_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_sub_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_such_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_sure_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_take_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_talk_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_tape_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_team_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_tell_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_thin_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_third_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_thought_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_thumb_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_time_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_tip_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_tire_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_ton_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_tool_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_tough_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_turn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_vine_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_voice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_void_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_vote_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_wag_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_walk_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_wash_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_week_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_wheat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_when_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_which_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_whip_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_white_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_wife_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_wire_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_witch_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_yearn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_yes_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_young_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Fear/OAF_youth_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_back_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_bar_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_base_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_bath_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_bean_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_beg_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_bite_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_boat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_bone_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_book_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_bought_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_burn_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_cab_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_calm_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_came_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_cause_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_chain_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_chair_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_chalk_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_chat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_check_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_cheek_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_chief_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_choice_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_cool_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_dab_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_date_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_dead_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_death_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_deep_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_dime_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_dip_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_ditch_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_dodge_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_dog_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_doll_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_door_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_fail_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_fall_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_far_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_fat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_fit_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_five_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_food_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_gap_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_gas_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_gaze_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_germ_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_get_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_gin_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_goal_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_good_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_goose_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_gun_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_half_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hall_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hash_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hate_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_have_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_haze_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hire_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hit_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hole_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_home_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hurl_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_hush_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_jail_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_jar_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_join_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_judge_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_jug_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_juice_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_keen_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_keep_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_keg_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_kick_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_kill_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_king_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_kite_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_knock_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_late_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_laud_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_lean_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_learn_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_lease_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_lid_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_life_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_limb_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_live_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_loaf_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_long_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_lore_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_lose_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_lot_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_love_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_luck_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_make_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_match_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_merge_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_mess_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_met_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_mill_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_mob_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_vote_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_wheat_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_wire_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_yearn_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Pleasant_surprise/OAF_youth_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_back_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_bar_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_base_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_bath_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_bean_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_beg_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_bite_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_boat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_bone_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_book_sad.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_burn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_cab_sad.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_cause_sad.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_chair_sad.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_lid_sad.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_limb_sad.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_loaf_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_long_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_lore_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_lose_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_lot_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_love_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_luck_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_make_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_match_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_merge_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mess_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_met_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mill_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mob_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mode_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mood_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_moon_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mop_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_mouse_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_nag_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_name_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_near_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_neat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_nice_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_note_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_numb_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pad_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_page_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pain_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pass_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pearl_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_peg_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_perch_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_phone_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pick_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pike_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pole_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_pool_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_puff_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rag_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_raid_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rain_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_raise_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_reach_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_read_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_red_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_ring_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_ripe_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_road_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_room_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rose_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rot_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rough_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_rush_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_said_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_sail_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_search_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_seize_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_sell_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_shack_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_shall_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_shawl_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_sheep_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_shirt_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_should_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_shout_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_size_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_soap_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_soup_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_sour_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_south_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_sub_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_such_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_sure_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_take_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_talk_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_tape_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_team_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_tell_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_thin_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_third_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_thought_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_thumb_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_time_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_tip_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_tire_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_ton_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_tool_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_tough_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_turn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_vine_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_voice_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_void_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_vote_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_wag_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_walk_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_wash_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_week_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_wheat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_when_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_which_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_whip_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_white_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_wife_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_wire_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_witch_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_yearn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_yes_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_young_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_Sad/OAF_youth_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_back_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_bar_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_base_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_bath_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_bean_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_beg_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_bite_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_boat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_bone_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_book_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_bought_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_burn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_cab_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_calm_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_came_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_cause_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_chain_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_chair_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_chalk_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_chat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_check_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_cheek_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_chief_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_choice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_cool_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_dab_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_date_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_dead_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_death_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_deep_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_dime_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_dip_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_ditch_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_dodge_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_dog_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_doll_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_door_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_fail_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_fall_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_far_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_fat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_fit_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_five_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_food_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_gap_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_gas_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_gaze_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_germ_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_get_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_gin_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_goal_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_good_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_goose_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_gun_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_half_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hall_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hash_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hate_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_have_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_haze_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hire_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hit_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hole_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_home_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hurl_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_hush_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_jail_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_jar_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_join_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_judge_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_jug_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_juice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_keen_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_keep_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_keg_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_kick_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_kill_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_king_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_kite_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_knock_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_late_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_laud_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_lean_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_learn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_lease_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_lid_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_life_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_limb_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_live_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_loaf_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_long_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_lore_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_lose_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_lot_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_love_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_luck_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_make_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_match_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_merge_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mess_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_met_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mill_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mob_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mode_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mood_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_moon_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mop_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_mouse_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_nag_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_name_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_near_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_neat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_nice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_note_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_numb_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pad_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_page_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pain_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pass_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pearl_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_peg_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_perch_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_phone_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pick_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pike_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pole_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_pool_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_puff_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rag_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_raid_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rain_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_raise_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_reach_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_read_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_red_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_ring_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_ripe_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_road_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_room_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rose_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rot_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rough_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_rush_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_said_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_sail_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_search_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_seize_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_sell_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_shack_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_shall_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_shawl_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_sheep_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_shirt_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_should_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_shout_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_size_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_soap_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_soup_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_sour_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_south_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_sub_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_such_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_sure_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_take_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_talk_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_tape_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_team_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_tell_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_thin_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_third_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_thought_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_thumb_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_time_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_tip_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_tire_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_ton_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_tool_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_tough_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_turn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_vine_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_voice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_void_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_vote_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_wag_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_walk_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_wash_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_week_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_wheat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_when_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_which_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_whip_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_white_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_wife_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_wire_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_witch_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_yearn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_yes_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_young_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_angry/OAF_youth_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_back_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_bar_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_base_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_bath_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_bean_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_beg_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_bite_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_boat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_bone_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_book_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_bought_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_burn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_cab_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_calm_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_came_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_cause_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_chain_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_chair_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_chalk_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_chat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_check_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_cheek_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_chief_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_choice_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_cool_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_dab_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_date_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_dead_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_death_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_deep_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_dime_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_dip_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_ditch_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_dodge_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_dog_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_doll_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_door_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_fail_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_fall_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_far_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_fat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_fit_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_five_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_food_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_gap_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_gas_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_gaze_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_germ_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_get_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_gin_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_goal_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_good_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_goose_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_gun_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_half_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hall_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hash_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hate_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_have_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_haze_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hire_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hit_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hole_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_home_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hurl_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_hush_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_jail_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_jar_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_join_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_judge_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_jug_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_juice_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_keen_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_kite_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_knock_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_late_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_laud_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_learn_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_life_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_limb_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_long_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_lose_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_lot_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_love_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_luck_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_make_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_merge_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_mill_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_moon_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_mop_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_mouse_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_nag_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_name_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_near_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_neat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_nice_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_numb_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pad_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_page_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pain_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pass_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pearl_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_peg_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_perch_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_phone_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pick_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pike_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pole_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_pool_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_puff_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rag_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_raid_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rain_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_raise_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_reach_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_read_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_red_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_ring_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_ripe_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_road_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_room_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rose_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rot_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rough_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_rush_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_said_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_sail_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_search_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_seize_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_sell_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_shack_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_shall_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_shawl_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_sheep_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_shirt_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_should_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_shout_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_size_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_soap_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_soup_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_sour_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_south_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_sub_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_such_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_sure_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_take_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_talk_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_tape_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_team_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_tell_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_thin_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_third_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_thought_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_thumb_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_time_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_tip_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_tire_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_ton_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_tool_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_tough_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_turn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_vine_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_voice_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_void_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_vote_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_wag_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_walk_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_wash_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_week_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_wheat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_when_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_which_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_whip_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_white_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_wife_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_wire_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_witch_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_yearn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_yes_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_young_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_disgust/OAF_youth_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_back_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_bar_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_base_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_bath_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_bean_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_beg_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_bite_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_boat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_bone_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_book_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_bought_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_burn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_cab_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_calm_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_came_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_cause_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_chain_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_chair_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_chalk_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_chat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_check_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_cheek_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_chief_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_choice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_cool_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_dab_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_date_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_dead_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_death_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_deep_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_dime_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_dip_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_ditch_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_dodge_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_dog_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_doll_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_door_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_fail_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_fall_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_far_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_fat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_fit_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_five_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_food_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_gap_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_gas_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_gaze_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_germ_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_get_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_gin_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_goal_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_good_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_goose_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_gun_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_half_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hall_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hash_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hate_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_have_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_haze_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hire_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hit_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hole_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_home_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hurl_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_hush_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_jail_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_jar_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_join_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_judge_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_jug_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_juice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_keen_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_keep_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_keg_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_kick_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_kill_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_king_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_kite_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_knock_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_late_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_laud_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_lean_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_learn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_lease_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_lid_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_life_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_limb_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_live_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_loaf_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_long_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_lore_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_lose_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_lot_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_love_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_luck_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_make_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_match_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_merge_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mess_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_met_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mill_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mob_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mode_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mood_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_moon_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mop_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_mouse_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_nag_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_name_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_near_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_neat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_nice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_note_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_numb_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pad_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_page_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pain_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pass_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pearl_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_peg_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_perch_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_phone_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pick_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pike_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pole_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_pool_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_puff_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rag_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_raid_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rain_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_raise_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_reach_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_read_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_red_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_ring_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_ripe_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_road_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_room_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rose_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rot_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rough_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_rush_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_said_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_sail_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_search_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_seize_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_sell_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_shack_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_shall_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_shawl_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_sheep_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_shirt_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_should_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_shout_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_size_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_soap_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_soup_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_sour_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_south_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_sub_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_such_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_sure_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_take_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_talk_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_tape_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_team_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_tell_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_thin_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_third_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_thought_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_thumb_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_time_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_tip_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_tire_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_ton_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_tool_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_tough_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_turn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_vine_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_voice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_void_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_vote_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_wag_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_walk_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_wash_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_week_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_wheat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_when_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_which_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_whip_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_white_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_wife_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_wire_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_witch_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_yearn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_yes_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_young_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_happy/OAF_youth_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_back_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_bar_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_base_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_bath_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_bean_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_beg_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_boat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_bone_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_book_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_bought_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_burn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_cab_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_calm_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_came_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_cause_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_chain_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_chair_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_chalk_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_chat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_check_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_cheek_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_chief_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_choice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_cool_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_dab_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_date_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_dead_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_death_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_deep_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_dime_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_dip_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_ditch_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_dodge_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_dog_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_doll_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_door_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_fail_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_fall_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_far_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_fat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_fit_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_five_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_food_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_gap_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_gas_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_gaze_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_germ_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_get_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_gin_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_goal_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_good_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_goose_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_gun_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_half_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hall_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hash_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hate_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_have_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_haze_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hire_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hit_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hole_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_home_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hurl_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_hush_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_jail_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_jar_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_join_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_judge_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_jug_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_juice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_keen_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_keep_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_keg_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_kick_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_kill_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_king_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_kite_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_knock_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_late_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_laud_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_lean_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_learn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_lease_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_lid_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_life_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_limb_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_live_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_loaf_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_long_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_lore_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_lose_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_lot_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_love_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_luck_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_make_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_match_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_merge_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mess_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_met_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mill_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mob_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mode_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mood_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_moon_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mop_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_mouse_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_nag_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_name_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_near_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_neat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_nice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_note_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_numb_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pad_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_page_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pain_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pass_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pearl_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_peg_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_perch_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_phone_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pick_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pike_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pole_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_pool_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_puff_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rag_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_raid_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rain_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_raise_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_reach_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_read_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_red_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_ring_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_ripe_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_road_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_room_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rose_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rot_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rough_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_rush_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_said_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_sail_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_search_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_seize_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_sell_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_shack_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_shall_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_shawl_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_sheep_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_shirt_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_should_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_shout_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_size_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_soap_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_soup_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_sour_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_south_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_sub_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_such_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_sure_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_take_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_talk_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_tape_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_team_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_tell_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_thin_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_third_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_thought_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_thumb_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_time_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_tip_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_tire_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_ton_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_tool_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_tough_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_turn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_vine_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_voice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_void_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_vote_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_wag_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_walk_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_wash_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_week_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_wheat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_when_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_which_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_whip_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_white_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_wife_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_wire_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_witch_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_yearn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_yes_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_young_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OAF_youth_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/OAF_neutral/OA_bite_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_back_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_bar_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_base_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_bath_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_bean_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_beg_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_bite_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_boat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_bone_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_book_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_bought_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_burn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_cab_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_calm_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_came_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_cause_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_chain_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_chair_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_chalk_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_chat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_check_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_cheek_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_chief_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_choice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_cool_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_dab_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_date_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_dead_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_death_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_deep_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_dime_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_dip_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_ditch_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_dodge_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_dog_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_doll_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_door_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_fail_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_fall_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_far_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_fat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_fit_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_five_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_food_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_gap_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_gas_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_gaze_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_germ_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_get_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_gin_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_goal_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_good_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_goose_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_gun_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_half_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hall_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hash_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hate_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_have_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_haze_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hire_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hit_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hole_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_home_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hurl_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_hush_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_jail_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_jar_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_join_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_judge_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_jug_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_juice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_keen_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_keep_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_keg_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_kick_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_kill_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_king_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_kite_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_knock_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_late_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_laud_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_lean_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_learn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_lease_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_lid_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_life_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_limb_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_live_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_loaf_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_long_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_lore_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_lose_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_lot_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_love_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_luck_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_make_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_match_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_merge_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mess_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_met_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mill_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mob_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mode_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mood_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_moon_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mop_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_mouse_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_nag_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_name_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_near_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_neat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_nice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_note_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_numb_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pad_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_page_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pain_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pass_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pearl_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_peg_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_perch_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_phone_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pick_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pike_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pole_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_pool_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_puff_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rag_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_raid_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rain_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_raise_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_reach_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_read_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_red_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_ring_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_ripe_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_road_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_room_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rose_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rot_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rough_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_rush_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_said_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_sail_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_search_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_seize_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_sell_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_shack_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_shall_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_shawl_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_sheep_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_shirt_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_should_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_shout_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_size_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_soap_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_soup_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_sour_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_south_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_sub_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_such_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_sure_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_take_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_talk_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_tape_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_team_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_tell_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_thin_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_third_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_thought_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_thumb_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_time_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_tip_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_tire_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_ton_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_tool_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_tough_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_turn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_vine_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_voice_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_void_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_vote_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_wag_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_walk_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_wash_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_week_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_wheat_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_when_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_which_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_whip_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_white_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_wife_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_wire_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_witch_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_yearn_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_yes_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_young_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_angry/YAF_youth_angry.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_back_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_bar_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_base_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_bath_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_bean_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_beg_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_bite_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_boat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_bone_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_book_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_bought_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_burn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_cab_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_calm_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_came_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_cause_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_chain_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_chair_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_chalk_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_chat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_check_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_cheek_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_chief_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_choice_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_cool_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_dab_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_date_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_dead_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_death_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_deep_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_dime_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_dip_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_ditch_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_dodge_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_dog_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_doll_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_door_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_fail_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_fall_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_far_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_fat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_fit_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_five_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_food_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_gap_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_gas_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_gaze_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_germ_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_get_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_goose_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_gun_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_half_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_hash_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_hate_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_have_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_haze_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_jail_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_jar_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_join_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_keg_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_kite_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_knock_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_late_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_laud_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_learn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_lease_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_lid_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_life_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_limb_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_live_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_loaf_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_long_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_lore_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_lose_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_lot_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_love_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_luck_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_make_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_match_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_merge_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_met_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_mill_disgust.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_mode_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_mood_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_moon_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_mop_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_mouse_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_nag_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_name_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_near_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_neat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_nice_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_note_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_numb_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pad_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_page_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pain_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pass_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pearl_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_peg_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_perch_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_phone_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pick_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pike_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pole_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_pool_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_puff_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rag_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_raid_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rain_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_raise_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_reach_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_read_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_red_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_ring_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_ripe_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_road_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_room_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rose_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rot_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rough_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_rush_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_said_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_sail_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_search_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_seize_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_sell_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_shack_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_shall_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_shawl_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_sheep_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_shirt_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_should_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_shout_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_size_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_soap_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_soup_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_sour_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_south_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_sub_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_such_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_sure_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_take_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_talk_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_tape_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_team_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_tell_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_thin_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_third_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_thought_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_thumb_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_time_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_tip_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_tire_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_ton_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_tool_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_tough_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_turn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_vine_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_voice_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_void_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_vote_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_wag_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_walk_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_wash_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_week_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_wheat_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_when_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_which_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_whip_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_white_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_wife_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_wire_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_witch_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_yearn_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_yes_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_young_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_disgust/YAF_youth_disgust.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_back_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_bar_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_base_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_bath_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_bean_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_beg_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_bite_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_boat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_bone_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_book_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_bought_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_burn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_cab_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_calm_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_came_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_cause_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_chain_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_chair_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_chalk_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_chat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_check_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_cheek_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_chief_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_choice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_cool_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_dab_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_date_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_dead_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_death_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_deep_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_dime_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_dip_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_ditch_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_dodge_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_dog_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_doll_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_door_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_fail_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_fall_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_far_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_fat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_fit_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_five_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_food_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_gap_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_gas_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_gaze_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_germ_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_get_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_gin_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_goal_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_good_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_goose_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_gun_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_half_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hall_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hash_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hate_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_have_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_haze_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hire_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hit_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hole_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_home_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hurl_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_hush_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_jail_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_jar_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_join_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_judge_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_jug_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_juice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_keen_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_keep_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_keg_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_kick_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_kill_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_king_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_kite_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_knock_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_late_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_laud_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_lean_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_learn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_lease_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_lid_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_life_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_limb_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_live_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_loaf_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_long_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_lore_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_lose_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_lot_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_love_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_luck_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_make_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_match_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_merge_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mess_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_met_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mill_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mob_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mode_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mood_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_moon_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mop_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_mouse_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_nag_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_name_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_near_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_neat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_nice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_note_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_numb_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pad_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_page_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pain_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pass_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pearl_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_peg_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_perch_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_phone_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pick_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pike_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pole_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_pool_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_puff_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rag_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_raid_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rain_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_raise_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_reach_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_read_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_red_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_ring_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_ripe_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_road_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_room_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rose_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rot_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rough_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_rush_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_said_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_sail_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_search_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_seize_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_sell_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_shack_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_shall_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_shawl_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_sheep_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_shirt_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_should_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_shout_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_size_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_soap_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_soup_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_sour_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_south_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_sub_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_such_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_sure_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_take_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_talk_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_tape_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_team_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_tell_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_thin_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_third_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_thought_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_thumb_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_time_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_tip_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_tire_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_ton_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_tool_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_tough_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_turn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_vine_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_voice_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_void_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_vote_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_wag_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_walk_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_wash_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_week_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_wheat_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_when_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_which_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_whip_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_white_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_wife_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_wire_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_witch_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_yearn_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_yes_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_young_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_fear/YAF_youth_fear.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_back_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_bar_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_base_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_bath_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_bean_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_beg_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_bite_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_boat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_bone_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_book_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_bought_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_burn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_cab_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_calm_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_came_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_cause_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_chain_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_chair_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_chalk_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_chat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_check_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_cheek_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_chief_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_choice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_cool_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_dab_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_date_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_dead_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_death_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_deep_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_dime_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_dip_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_ditch_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_dodge_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_dog_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_doll_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_door_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_fail_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_fall_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_far_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_fat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_fit_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_five_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_food_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_gap_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_gas_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_gaze_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_germ_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_get_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_gin_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_goal_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_good_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_goose_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_gun_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_half_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hall_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hash_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hate_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_have_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_haze_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hire_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hit_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hole_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_home_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hurl_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_hush_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_jail_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_jar_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_join_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_judge_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_jug_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_juice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_keen_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_keep_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_keg_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_kick_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_kill_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_king_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_kite_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_knock_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_late_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_laud_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_lean_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_learn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_lease_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_lid_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_life_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_limb_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_live_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_loaf_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_long_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_lore_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_lose_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_lot_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_love_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_luck_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_make_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_match_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_merge_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mess_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_met_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mill_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mob_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mode_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mood_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_moon_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mop_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_mouse_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_nag_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_name_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_near_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_neat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_nice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_note_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_numb_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pad_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_page_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pain_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pass_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pearl_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_peg_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_perch_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_phone_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pick_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pike_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pole_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_pool_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_puff_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rag_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_raid_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rain_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_raise_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_reach_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_read_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_red_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_ring_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_ripe_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_road_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_room_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rose_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rot_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rough_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_rush_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_said_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_sail_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_search_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_seize_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_sell_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_shack_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_shall_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_shawl_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_sheep_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_shirt_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_should_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_shout_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_size_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_soap_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_soup_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_sour_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_south_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_sub_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_such_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_sure_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_take_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_talk_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_tape_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_team_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_tell_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_thin_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_third_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_thought_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_thumb_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_time_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_tip_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_tire_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_ton_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_tool_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_tough_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_turn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_vine_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_voice_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_void_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_vote_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_wag_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_walk_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_wash_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_week_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_wheat_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_when_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_which_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_whip_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_white_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_wife_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_wire_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_witch_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_yearn_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_yes_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_young_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_happy/YAF_youth_happy.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_back_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_bar_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_base_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_bath_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_bean_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_beg_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_bite_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_boat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_bone_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_book_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_bought_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_burn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_cab_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_calm_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_came_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_cause_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_chain_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_chair_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_chalk_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_chat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_check_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_cheek_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_chief_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_choice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_cool_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_dab_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_date_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_dead_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_death_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_deep_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_dime_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_dip_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_ditch_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_dodge_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_dog_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_doll_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_door_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_fail_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_fall_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_far_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_fat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_fit_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_five_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_food_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_gap_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_gas_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_gaze_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_germ_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_get_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_gin_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_goal_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_good_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_goose_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_gun_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_half_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hall_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hash_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hate_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_have_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_haze_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hire_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hit_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hole_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_home_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hurl_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_hush_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_jail_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_jar_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_join_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_judge_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_jug_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_juice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_keen_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_keep_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_keg_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_kick_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_kill_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_king_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_kite_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_knock_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_late_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_laud_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_lean_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_learn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_lease_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_lid_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_life_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_limb_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_live_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_loaf_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_long_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_lore_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_lose_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_lot_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_love_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_luck_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_make_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_match_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_merge_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mess_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_met_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mill_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mob_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mode_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mood_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_moon_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mop_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_mouse_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_nag_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_name_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_near_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_neat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_nice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_note_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_numb_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pad_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_page_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pain_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pass_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pearl_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_peg_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_perch_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_phone_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pick_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pike_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pole_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_pool_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_puff_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rag_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_raid_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rain_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_raise_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_reach_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_read_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_red_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_ring_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_ripe_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_road_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_room_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rose_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rot_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rough_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_rush_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_said_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_sail_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_search_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_seize_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_sell_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_shack_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_shall_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_shawl_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_sheep_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_shirt_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_should_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_shout_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_size_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_soap_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_soup_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_sour_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_south_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_sub_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_such_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_sure_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_take_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_talk_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_tape_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_team_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_tell_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_thin_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_third_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_thought_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_thumb_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_time_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_tip_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_tire_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_ton_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_tool_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_tough_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_turn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_vine_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_voice_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_void_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_vote_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_wag_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_walk_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_wash_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_week_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_wheat_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_when_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_which_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_whip_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_white_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_wife_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_wire_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_witch_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_yearn_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_yes_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_young_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_neutral/YAF_youth_neutral.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_back_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bar_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_base_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bath_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bean_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_beg_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bite_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_boat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bone_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_book_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_bought_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_burn_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cab_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_calm_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_came_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cause_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chain_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chair_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chalk_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_check_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_cheek_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_chief_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_choice_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_learn_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lease_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_lid_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_life_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_limb_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_live_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_loaf_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_long_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_love_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_luck_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_make_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_met_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mill_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mood_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_moon_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_mouse_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_nag_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_name_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_near_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_neat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_nice_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_note_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_numb_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pad_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_page_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pain_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pass_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pearl_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_peg_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_perch_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_phone_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pick_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pole_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_pool_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_puff_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_raid_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rain_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_raise_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_reach_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_read_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_red_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ring_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ripe_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_road_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_room_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rose_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rot_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_rush_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sail_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_search_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_seize_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sell_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shack_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shall_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shawl_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sheep_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shirt_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_should_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_shout_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_size_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_soap_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_soup_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sub_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_such_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_sure_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_take_ps.wav \n",
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" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tape_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_team_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tell_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_thin_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_third_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_thought_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_thumb_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_time_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tip_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tire_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_ton_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tool_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_tough_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_turn_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_vine_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_voice_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_void_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_vote_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wag_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_walk_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wash_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_week_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wheat_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_when_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_which_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_whip_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_white_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wife_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_wire_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_witch_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_yearn_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_yes_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_young_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_pleasant_surprised/YAF_youth_ps.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_back_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_bar_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_base_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_bath_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_bean_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_beg_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_bite_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_boat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_bone_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_book_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_bought_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_burn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_cab_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_calm_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_came_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_cause_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_chain_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_chair_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_chalk_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_chat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_check_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_cheek_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_chief_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_choice_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_cool_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_dab_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_date_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_dead_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_death_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_deep_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_dime_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_dip_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_ditch_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_dodge_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_dog_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_doll_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_door_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_fail_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_fall_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_far_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_fat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_fit_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_five_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_food_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_gap_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_gas_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_gaze_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_germ_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_get_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_gin_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_goal_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_good_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_goose_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_gun_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_half_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hall_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hash_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hate_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_have_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_haze_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hire_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hit_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hole_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_home_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hurl_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_hush_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_jail_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_jar_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_join_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_judge_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_jug_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_juice_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_keen_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_keep_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_keg_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_kick_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_kill_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_king_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_kite_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_knock_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_late_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_laud_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_lean_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_learn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_lease_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_lid_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_life_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_limb_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_live_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_loaf_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_long_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_lore_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_lose_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_lot_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_love_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_luck_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_make_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_match_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_merge_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mess_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_met_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mill_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mob_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mode_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mood_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_moon_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mop_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_mouse_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_nag_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_name_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_near_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_neat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_nice_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_note_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_numb_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pad_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_page_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pain_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pass_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pearl_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_peg_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_perch_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_phone_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pick_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pike_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pole_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_pool_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_puff_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rag_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_raid_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rain_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_raise_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_reach_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_read_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_red_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_ring_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_ripe_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_road_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_room_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rose_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rot_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rough_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_rush_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_said_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_sail_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_search_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_seize_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_sell_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_shack_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_shall_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_shawl_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_sheep_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_shirt_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_should_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_shout_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_size_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_soap_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_soup_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_sour_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_south_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_sub_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_such_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_sure_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_take_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_talk_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_tape_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_team_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_tell_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_thin_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_third_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_thought_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_thumb_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_time_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_tip_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_tire_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_ton_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_tool_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_tough_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_turn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_vine_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_voice_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_void_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_vote_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_wag_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_walk_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_wash_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_week_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_wheat_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_when_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_which_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_whip_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_white_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_wife_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_wire_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_witch_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_yearn_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_yes_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_young_sad.wav \n",
" inflating: tess toronto emotional speech set data/TESS Toronto emotional speech set data/YAF_sad/YAF_youth_sad.wav \n"
]
}
]
},
{
"cell_type": "code",
"source": [
"Main_WAV_Path = Path('TESS Toronto emotional speech set data')"
],
"metadata": {
"id": "ChRdzEW2pvHr"
},
"execution_count": 5,
"outputs": []
},
{
"cell_type": "code",
"source": [
"Wav_Path = list(Main_WAV_Path.glob(r'**/*.wav'))"
],
"metadata": {
"id": "YjbH5a__qRNK"
},
"execution_count": 6,
"outputs": []
},
{
"cell_type": "code",
"source": [
"Wav_Labels = list(map(lambda x: os.path.split(os.path.split(x)[0])[1], Wav_Path))"
],
"metadata": {
"id": "ucVZk-WtqW0B"
},
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"source": [
"Wav_Path_Series = pd.Series(Wav_Path, name='WAV').astype(str)\n",
"Wav_Labels_Series = pd.Series(Wav_Labels, name='EMOTION')"
],
"metadata": {
"id": "Okodfks1qnrW"
},
"execution_count": 8,
"outputs": []
},
{
"cell_type": "code",
"source": [
"Main_Wav_Data = pd.concat([Wav_Path_Series,Wav_Labels_Series], axis=1)\n",
"Main_Wav_Data.head(5)"
],
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"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "-vdnHT51qub7",
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{
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" WAV EMOTION\n",
"0 TESS Toronto emotional speech set data/OAF_ang... OAF_angry\n",
"1 TESS Toronto emotional speech set data/OAF_ang... OAF_angry\n",
"2 TESS Toronto emotional speech set data/OAF_ang... OAF_angry\n",
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"4 TESS Toronto emotional speech set data/OAF_ang... OAF_angry"
],
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" <td>OAF_angry</td>\n",
" </tr>\n",
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" <th>3</th>\n",
" <td>TESS Toronto emotional speech set data/OAF_ang...</td>\n",
" <td>OAF_angry</td>\n",
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"cell_type": "code",
"source": [
"Main_Wav_Data['EMOTION'].value_counts()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "aD7SPRfCq8tZ",
"outputId": "2c0e5d18-6cd3-44a8-b888-2225f5c0c9f9"
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"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"OAF_angry 200\n",
"YAF_disgust 200\n",
"OAF_Sad 200\n",
"YAF_fear 200\n",
"YAF_happy 200\n",
"OAF_Fear 200\n",
"OAF_Pleasant_surprise 200\n",
"OAF_neutral 200\n",
"YAF_sad 200\n",
"OAF_happy 200\n",
"YAF_neutral 200\n",
"YAF_angry 200\n",
"OAF_disgust 200\n",
"YAF_pleasant_surprised 200\n",
"Name: EMOTION, dtype: int64"
]
},
"metadata": {},
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}
]
},
{
"cell_type": "code",
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"Main_Wav_Data = Main_Wav_Data.sample(frac=1).reset_index(drop=True)\n",
"Main_Wav_Data.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
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"id": "cIeBnGzPq9aJ",
"outputId": "076159b4-ff92-4146-ef5f-ca648b2a5754"
},
"execution_count": 11,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" WAV EMOTION\n",
"0 TESS Toronto emotional speech set data/OAF_dis... OAF_disgust\n",
"1 TESS Toronto emotional speech set data/YAF_hap... YAF_happy\n",
"2 TESS Toronto emotional speech set data/YAF_fea... YAF_fear\n",
"3 TESS Toronto emotional speech set data/OAF_neu... OAF_neutral\n",
"4 TESS Toronto emotional speech set data/OAF_hap... OAF_happy"
],
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"\n",
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"</style>\n",
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>WAV</th>\n",
" <th>EMOTION</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>TESS Toronto emotional speech set data/OAF_dis...</td>\n",
" <td>OAF_disgust</td>\n",
" </tr>\n",
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" <td>TESS Toronto emotional speech set data/YAF_hap...</td>\n",
" <td>YAF_happy</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>TESS Toronto emotional speech set data/YAF_fea...</td>\n",
" <td>YAF_fear</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>TESS Toronto emotional speech set data/OAF_neu...</td>\n",
" <td>OAF_neutral</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>TESS Toronto emotional speech set data/OAF_hap...</td>\n",
" <td>OAF_happy</td>\n",
" </tr>\n",
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" width=\"24px\">\n",
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" fill: #174EA6;\n",
" }\n",
"\n",
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" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-68c6ab28-f5c5-4337-9e52-04627741d36d button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-68c6ab28-f5c5-4337-9e52-04627741d36d');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 11
}
]
},
{
"cell_type": "markdown",
"source": [
"# <a name='EDA'></a>\n",
"\n",
"<div style=\"border-radius:10px;\n",
" background-color:#ffffff;\n",
" border-style: solid;\n",
" border-color: #0b0265;\n",
" letter-spacing:0.5px;\">\n",
"\n",
"<center><h3 style=\"padding: 5px 0px; color:#0b0265; font-weight: bold; font-family: Cursive\">\n",
"2. EDA</h3></center>\n",
"</div>\n",
"\n",
"<a href=\"#toc\" class=\"btn btn-primary btn-sm\" role=\"button\" aria-pressed=\"true\" style=\"color:white\" data-toggle=\"popover\">Back to Table of Contents</a>"
],
"metadata": {
"id": "7N_2JOi42clH"
}
},
{
"cell_type": "markdown",
"source": [
"Examples of Audios"
],
"metadata": {
"id": "cuHKsc5OteM_"
}
},
{
"cell_type": "code",
"source": [
"rate, speech = read(Main_Wav_Data['WAV'][2342])\n",
"print(Main_Wav_Data['EMOTION'][2342])\n",
"\n",
"Audio(speech, rate=rate, autoplay=False)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "GiD0O54-q9HF",
"outputId": "cfce33cc-52b6-454a-f274-7864172f9d13"
},
"execution_count": 12,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"YAF_neutral\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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" "
]
},
"metadata": {},
"execution_count": 12
}
]
},
{
"cell_type": "code",
"source": [
"rate,speech = read(Main_Wav_Data['WAV'][2342])\n",
"print(Main_Wav_Data['EMOTION'][2342])\n",
"print(speech.shape)\n",
"print(speech.dtype)\n",
"print(rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "C0iv9MCjto_P",
"outputId": "27b8b090-07f2-48f3-bfc5-9dcec50e6cc2"
},
"execution_count": 13,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"YAF_neutral\n",
"(50823,)\n",
"int16\n",
"24414\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"rate, speech = read(Main_Wav_Data['WAV'][10])\n",
"print(Main_Wav_Data['EMOTION'][10])\n",
"\n",
"Audio(speech, rate=rate, autoplay=False)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "MzkDhC3uq9Eh",
"outputId": "e96d45d6-8879-46f4-db12-0a65e109fefe"
},
"execution_count": 14,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"OAF_angry\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
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/MwCPwleAOMAjgLU/gkCWQId/w8DsgDF/4b/MwFiBHcE7AJn/n0AtQGcAQ0GPARD++MAYQVyAUf/4wBDCHYA2gLR/WwKL/55/lP9yQJEApcE8QBBAfP/7P+q/SUGnAd2AXD38wKUA0IAvv+mAvv93v/UBj0CtwK1ANoCsf5VA+4E9AX4/OgDXAO5AH77gwcPCB4BAf+gAXH/qgcCAXn9PQIxBQH/NPxxA04DkgEv/5v/AQOs+4QAfQZeBT4B0QAZ+9gFLQpq/zv8+AWPBcX/UgL2//QB3v9vADAGcQMmBRABFAA+ARwEPAPz/5H+SQDABez/yQKVAVn/3Pw1BN4CR//mBYcBDvtUBKAFQP9oACAD9/6dAJ8CiwEPCBEF+v/f/Q0GsQZE/xcBjwVRAxkDzf0o/kUB8AHWBFEDVwDj/N8AXQITB/QA4vkiAFsKEgQQAl8EGwCq/s8I2AEsAkD/VQgU/bwFgQCK/4b/EwIKAIsBEgPTA/sFjPxDBKkDrf95/TQFkQdWAhkDSAEF/90DcASV/ln/jwWBAJIFiACHAkn8mP93BJADTAB0BKQAZQW0/vX3hABPDKwDn/mWBfgKWgGf/zoBNAAD/AoF/gZFBuYAcgG9/GACIAMY/bgHlgVMAd8ArQL0/aMBEwdb/Cz+vAuKAt75BAlIAnr8MAFmA+AE+gIFAsgD6AL6/0j+xQIa/8oFZQXYAU7/lAP4BWEAqv2K/t0DzwSHBlwDpQOY+U7/SAeZBSMEiwWR/2cCYwPO/EADoQT3/Qn+XAOZBlAFtvwY/VYCNQRV/yUGpwYXAY8A6AKLBacARP8tBUYKPgF9AFn+cgYVBfcBHvkNAKL/ZgRqCDgFcPtp++0BvAbmAA//pwVYA2wA4wVKAx0DSgOc/Q0AQgpJBaMBEf0XAoQA+gIZBPAMzAL++Kn/VgszAsMB5AMpACD7jATRAWMDkf4CAqoGPQem/5cDwwHv/yQD5gWm/+EC4gE2Ai8CAwCY/rcIIQI4/HgIgAuV+Ar3eQeAB1MAuP7WCZL9nAagCgkCOPv7Bu0AK/rDBiYK/PtR+50FtAJe/OUCMwalBO8Cef1S/3QEHAkUAez/Bf+HAkoEnwdgB+D8Kf0SCJcE0/8r/xAH7QZ1/5ADTAV5/gYAXgXTAwMArf5gB1oGdf5a/U8CeQESBIAMbAU29MgDtAftBQX/tP+zAzsKKALoA6kChP30ADYCrgF8AhgA6wPvApMJGwGV+Rb6qhFkBxT9CwPbBsL5nAEZDtoCivpH/9gG1gTjBeL9DP9kAggDT/6ZANoIkgYEBDT8Vv61BUD/agMkCF79Iv21CnYFmQFnAogA7wKbA6MB2gMuA40DjQNJAOAEuP6cAq4KAQNg+W4CPAj0AO0AlQHYAEYEowcSA2kEFABb+wAEwACnAZUHgAZ8+tsBnwedAB0DswSsA0j+fQDaB48FlP+qB8L+u/lNCagJcgEnBG0Dk/wqBU0EH/0PCFkC0PkRBXENCf6Q+54EHQi+AgYBdgETAnYKfQAs/qoHGwEF/xkIEAZN/AkGtf3MAkQCQQZ8+Y8A3wVkB4r+YgnbAfn7VQMeB14AEAYvB/v9XvxIBqICkgE1BFMGxv0y/+kGPwpq/wj/7QUN/VYGtQtW/pUBuwcwAeMAyAit/u0B/gZQCt75n/+8ABAHoQTQAtz8JP+TBEMJXQFdAn8DJgDC/qwIyASA/WsBrgv/ALf6FQUpC8cAYP4RBe4EQQEgCNYDEQB1+jkDEgns/okJIgEj/AL+wQjaAnsEzP+pCCYAHwD+BnAEyf7GARIEkQJ2BTABNgf+/RACggTC/4EAVgaOAtkEzgX7AAkC8AElAk8BCwgzApsDJQHTA08CTAbF/xYD6wgGAGQBvwefB4f59QRVA6MBKgWCBN8BkANBAZgHHATi+VkCjgYnCYsBpwULAzcBwv8NBlAA9gMOBMwCkPs4CQIGjwAz/iUBIwnqBcj6qgaoCW8BTv8fALT//wUIDUD/sf6aCUUBM/7rA2UF7P6QA2EGvwHdAzwEJf7hB9UFhP3pAXAEOgvW+zv8VwrCAvD5nQqSBbn82gPcBe0F9AEiAGUAzAPsAmEFyANzAGQBqQK2BEYEnQBtA48Fh/5KCX0BGQPmABUKDP8zARcCRQshAqn/bQSVBgQDo/4zAdoHGQTsAmwFaAFaAf8ArgUkAz4AAAAVBTQKVwUq/MwDhwGjAVMBWQcZA+EC5viKB20I8wLM/+MFCAPaArYERgSf/88DbQMiAfYCbgdrAb8BoAEgCH0A+QMLA0wFH/3DBUoIywS0/vkDMwyc+YsBdwQ/CV0B8QWW/DsAqQIOBdwAlgWZAVn/cwUHBQz/XQKXCSv/sf7gCQMFRP+mB1n/5gFhAUEG7gnAAIn7ZAbhAij/8gSfB9D+LgmG/xYD5/yZBjUI3/2W/HwMLwIz/kUGhwZs/LwG/v1FBsIH9v8vArACzQYo/5cIbgLMAnX/swMsAuoAoQkRBUUAvP0OCU4D6f2BCl0HEfy0/oAGfAwH+wb9wQnNAaP+oABKCDYCvwGq/soBlwR/CFEDkASc/gn+Sg4xBHz+aAU8Ax3/TQQrCPkEu/l5AnkGLAJ0AxgFWAP9B6/2a/7XDG76+wp+BDH8PQJRCKcBhv/WBNMIM/7x/JoJaQn7AI3/0f19Ae0F/QLbAUgB1gO1BTMCNP1MBlsERfi0B68ETwI6B4cBRPqpAkgLEAfF/3ED2wxFACv6EggFAs/7qwBEB9ACjgHSCbUFGPfrBLoD1P2wCDgJG/2Z/dMDTQm6CIf4L/6DDLwBhQQVCjb5p/0qDqID7vsF/54E6/q6DocCoADBA5v/sgB2Bu0FJQF+/NUFGRMJ9OX/rgvl/yj/Zwdp+0/+IA1WAaL6TQTvA8n+gweQAxACWgVG9owEhQ+V/W75SwwmBaL6cQjWBHH/MAZLAkD6AQP9AkcIJv03AbQHSf1s/HoKPgZl/KUJTAHpAbcIXgBY8cMQcwD+9OIMowfR+IQQYQbF9bwF6wmh9yAE+Q0Q+W4C7wjC9DwEURPM8NMCsA2x85UHww+G9fEFpwVv/WQCXgpC/eUCgwf+/tD/eQJvAN8FVQPC+rEGEAs+AGbwVgzABWf6wgejEJXvOQiLCqX2bwElC9/4kQIKCpkB3v/+/qoGKwgv9ND+uAxaAWcHvQSA+FsJkATl/4P+aAV6/MMFUwU6Amf+twhu/6/8Iv1vBtsGHwXW+8EJAPyV/U0K6goO9oEAXwlXABz74QdWApf7Xg8j+x8ALAb5BCADXwRU9koIxgGq+bgLCBIs+NLy7gliCmP62wtsCkbnUQRgEf79pv7MCLv+NPzMAwQOKvwUAVwN0vw99RQLoAEOBWEBpwCZ/ckCng2D/wD8ywRLAlYBkANX/RH4NQhrAu8Dm//T/y/+TQlrAsn+sQcUABb65w70BY79hgOAAQoA0AdS+q0HqATQ/q4A/QOA/UUFLP4h/48FMQVGBP/3CgAqCbkAL/4gCBD+QgAJAjkNB/YNBp0FD/9U/I0I0/81BFoGtALF/yb92AGZAKAGsALsAj0CqwBv/R0NiQPY+N8FOwAAABwPAPtA+ooMngio9t8A7QYOCt/4UwZTAIr+/vhwCdEBQgA8BG4CugnkBOL+dfnJB7MDyPuR/i//iv4LBHsEMwcm96D94Q02BzIDZ/kZBKb+4PsjCTUJkPEsAskMafxA+lsJLAI6/qcGYAKi/+gCqAky/4z8eQJc+kwA6gUuAzoBkAR9AIgFdPuc+DwEhgMW/w4F/f9i/A0GXgBRBAMFef5y/t4MtAJNCeYGjviZAScDSAHBA8gE9v+4BjoGXf7C/9wKWQKoBIkDK/9gAvYIzf5TABcHvfx69+gIfAcGAJILqvj194QK0wIm/BAM1vua++cJjv1l9yoF/f+p/77/SAFkAsoFyQKT/O3zs/uw/4f+dv3l/uz5RP5+BKL/o/4j/Mr9kgFhAL/+7wKZAKr9mP+V/gn+tP/KBS4EzQEDBW8AvgItBeMFtQDsAjkD+QmlBMQEXwhFAIYDWQz7BrUFiQ3vAgAFNgxhBgsEDwhACJwHtwMXB5sN4QNyBqUI6QGVApkK1gTkA04DRgToAjQApAUwAMT8FQRRBAH/h/2LAIP5T/klAfz7APcz+eoAxvl79sT38PmS+IX7Ivj5+gH6ovUc/FH7APcj++D7E/klAeX+VPuRAs0BuQAcBZcDiwHpBgMF2Aa/BgAFZghUCWcH7QaLBmIKLAvdCBwJjgfABQ0L/gvzB6wJmwhDCQ4KFwfdCawOXAhNCSgHLAYFB6QFDAKuANgACQE0BaYCv/1//0z9Ov4W/30BRP9k/T3+bv5V+kH5IPv19975tfiV9ET5Bfoz+HL01PPu8pv1y/bd+pb86/aS+Hf7Afpb/CL9QP/HAED/rgDPA/kDtP+pAm8FowafB78MAAp2BmgLfgm5ChQLfQojCU4N/gyhCTgKAwoICBUKkwkkDQENBwp9C+MKwgeAB74IqgaEBsMGIwWEBWcCegBDA2QB5f68/QX+If6J+xv4KvaQ9iz0jvQJ+SX07fN58wz0/fDG743w4u8E8avyzPWJ9srzDvYw+AP41Php/O778vq4/soAbAApAXsELghmCdYOJA1CD8oPFxCJDmUPFQ4xDywRgg4QEKAQBQz9DewM1wynCkMNJQy8CrYJ9Qm2CXIG6wTTCCYFiAU6Bv0D6f4P/5/+/v0P+q35RPo495XzxvOr8nDxxfAM77jvM/TE8RLx5PAP8KnrYu3P8Fvy7vEX9Bj4uPhE+gf7Gvpl/Hj/DALtAMYGJQJ4A0EH8glnB/cM5A7GEG0TRxLdEp4Srw47D+8Nkw9IDFEN/gxyCwwH0AdjCBkDVgZIBpAEpQOXA6cBJAO0AkMDewSLBkEGoAZrBkEGmAIQAY4B+v9u/kP7BPv0+P70qPIj8pDxSO499BX2RfN/8B7zxupg5YfpWe8c7UvwaPgm+Hn5a/58/sn5Av5LAokEiwZ3CfAGrQc2B5IKFQqUDVsPBRLQETMRIRECDJ8HTgizCNgGvwdKCBcGeAMeAhoCXP8YAHYAFADDAAoA9v8fAAAAZ//6AigH0QoQDOwMNQ5eCgEIzQaCBEv/ZQD3/vz78vbV9zT3HvNU8of0v/SZ82T0Xe8w6e/heeBk5K7pt+ve72f51vtC/Cj/bwFy/ksCYAc4CXQNygrNB7oIiwrICO8Nzg9iE/kThROoE3AOZgjcBZ0FvADiAQAAu/+D+sX6Hvkc9ib45vh1+j3+0P9v/YEA5gD0AGEBBAiqC1AP1hImFJQSAQ1kCyAIYQapAicDiACm/oD5r/ZS9dLy+u9R8dbxJe/G6qvjbd3I153ZCOY67sDtSPnBA8cAWQJkB7UF+QMVCu0QyRGTDzMR8AzpDPsQchEMEm4XQxgMFsETAw+8Buf8r/w0/Ab4RvYJ+e7yFO5w7Onqp+ig6RDv7fPA98X6zvwt/V4ArANfCYcRiRgTG7wfvSIKHjgZfBZpEx8PHA7NC3IGQQK+/4L7eveN9dr1zPXm8/7vB+2O5VLbotL3xue/k8kg3aDpOOyC+6QKEgihCbwQiQicB9YTEBU7FKwTKBF3Dr4SWRbzGwofQiRhH+EcHRdFC7z9MfLU7jrvmuyM7Yfveui35rvlD+Yo5VHn3ety85f1xvl0+3L4B/zEBKAQVxnPInwq6i0IMDIruCC4GyQX3hEbEJ4NYwiOAgX/rPvF9Rvz3vSM8UbxgvHU5YHeNdc7xVC7nrnWuZHRW+zi6Y/3JRXFEmELlRoIF80LehRbHr8WRBF2FaETDxIzG+0knybxKDYmLiL1GLMNYPq653bkI+Ow3BLhWuN+3TvefuK147DgUeIC6fTtA/JP+ef3TvXc/OIGWBKvHk8qrTTDPa0//zfHLuwmHRzHFAUSrg/VCrAC5v1p+83zIPEO8vfu7e0/7Y7kSNtzz97BVrfTrgCqWcLT4fLmYvI1E2sW0Q/UIEYiDxIDGpsmoB/OGRweNxrEFLUfQyxvKekqciq2I/4byREz+JHg/9mc2gvTU9TM1pnQ7dDA2e3ZCtkZ3DXimeio8db6Vfq++usE7QvZGAAomDCyPRtMP0s5RMU6rS9XI3MZxBS8EOMKrAOz+2H4SPQh78ftUeuM58/neuMA2DfLTb9us16mPZ58rtHPfuKa7ZcNHCLNG+Em3jSFIloarCxZKq0b6yIpJB0XgyA4MssteSqAL8opISHYFdb6NttW0GjPx8XewoTG3cNhxsXS9NUu0xbXfOCh503tlfNi99H4lwONDWIZNivvO5NLV1sEX/hWHk3EQVkv3B6QGCgRWQcsAYf5sfNN8aXsSuu16XPjieGf4KfV9sclvEavTqQJnZ6bzrBX1NPr5f5EIWsvuSj4OKY/KSS7IHgxQyerHuQneiOdHq0wST0LMWQv2DPBJyoZdwQE4rDIycG/vGm0SbbEuey8V8kM1mbTWtU94IPltOUz6gXr3ezi73b9UhF/K+FA3lg0cH55aW+2ZaJTsDrXKmAb6QvSCTEFvftZ+S/5rvPz7+3tCeRb3bTbFtL3wSi3N6wConKeQZlVlX6r49jQ+bwKvibFO+oy6jiWQTUn9heeLHctAiVLLxEyOC3+PltQnT1OLDQyjyNsCgX0LNVutwqxx7XtsTSwgrndw2XPFNlL1ubQzNfT3Iva+tty35XkRPCiA7MX5i5QTIxquXn/f9t6/2UPVNo/wiVPGnkVsw6lDu4JgwJj/wP8tu245AfeJ9MgzsPKOry1sa2tmqamnpacDJlfoOPEZPQICOsTSTO9PMou6zb/M8IWiSKRP143JzZHREpBy0HqUc1DQSWhI7cmRglk8xHeVL+IsOe6Drq2r6C2OchBy/TQ09FMxWnEM9Xb1crQotwx6JrxMQQ8GKIh9jDxUdNtN3AfcE9x2mPfUkhDvjBHISoijCOZFSMKkgUL+y/wv+QD2bDRnNAE0v3HsbxVucq2qK+QpWmgDJ7+nkiyUtaj+IMHrx3jPfo5gjF0QHM4bCPhQPtNzjikPO5LvDi5PJNB2yp8Fvomhxpf+1voN9XCt/+14LktsBGrU7vDxZjGNc2vyc7EsNKT3ejWbtuC673yqv6AECwa+SLqPcxZRmVpaRNsTWqXX9RSBj35LEQmvCSsHSgRfwgk/+P38O+J4QvXNdO30knPZ8HUtya1lK4oqP6jf58rn2Km5rsa4Gf/sBImJI9CpjmiNQBB7jzLI2hCZ065PYs9XU13N8w/Dz9lLV8S1SP3DC/vnt0hzIqt9bDnudCzOa5TwOrJuMY8zuXMJsV/zczcoteF3bHufPWyAPUZhCTCJRQ+cFqPZWpoqW3xattdsFN/QMwrhyXAI3kfQRFkBln/A/hU7Hzg6dU1zgjNdsoDu9K0V7WcrYymYKRPniKd1qoewf7krgG3FwMpDERzPYg4Oj7zOdksYUOUTklCy0GQS+o9uT3jON0nkxQFG4IEDuiN1y/H9a8hsr25orNhsZfDPsp5xrnJp8prxg3P4trm2XLgSPOi+vQG+RxYJ70t5kgqX9xl62lObZBkeFkUTCk5wyl6JHciCx3zEdgGL/909l3qDt2N0fbIMsc2wle1hLEDsaOn1qTGo0+efqBKtNXTzvdyDJUgkTVaQsk1zzv9O+8rKzXtTO9KbkQDTI1J0z90QMcuiRhlFLgQkPHd3YLSerq9sKa4qbjBr3W8ncpZx33G1cmtx/LIrNJt2ELZheyN+qcB4xSWKLQroD2gVwBfx2DdabFn/1tPUp5Auy9SKkMnSCBOF6cL3QOh+yPxtt3804PMzMd/wiK77rC4sYmvvKfYosSgz6Dnq+XGAesfBR4bJyyIQmk8sDayPQA3PSrKQlZNvkVRRrZLyT4+PvszCCGaDsYRrfqE5FHYyccqsDKzzrqktU21OceWyg/HwsukzjnM1c4G2Qvc7+VX96cAuAxXJDMvgDTnS5ZbQV2XY0RoaVvmTWJBFjAoKi8mQCGlGIINJQZE/z30QeSE1ZfNN8qAxiO/ZbbMs+e1ja77pw6lVKUmqwLBy+K7/3kVwSd7O7NADzXqOAw6OyjTNWhIv0O0P/hGwD1gOq839yTjD/4QoAF058nb+M/StYGx+LvruYG28cVzzoHJMM9K0nrPhM9c18XcY+Zw9qcAbQhOHJAsZjGCQI5SMlRUWr5j5lwpTW5E+jSrKXEmDiIgGIsQygYaAgP3ROpU2OHSIM4+yxzE5b0lt2q5o7cVsL6p06ncqy+4+8+58rsHyCIYLu9AojpjNlc4szFAJq49akR2Pt46rkK7NZ85dSvwGxwJPQyF8vnigNXjxD6x1rn8vs66YL3/zt7MkM121BjUgc9T1GPcYuJr7zH8QANyEBolhC7ZMpZGKVF0VNhcVGCIUblGyzwDLTImZSNwHYgU+AomBcv8kPFj4XjWDdDHzvzJwMAYu+66ULsKtZ6v4qg2raOyFMC/2mD5YxI8Jxgy0kGoN/QzGjrzK14pFkCsRcI5OTsuQFw1bTFLKqETTwd6BQft/9lH0vG/vLFZvL7DqLpOwo3SZMupzCXWe9K8y33VGN5P5ULyVf8QB8IWiisuMfY15UlBUpBVWV2AXbNLo0O0OQ4t+CMUJMgcnhL6B54ETff+6QTdq9TMzDvPccdqvU+8e772uNa0Fa8EqhqutbbkvtjZcPc3FWknqDJ8P3Q7ajUBOjsufysbPkVHizi4ObNA5TVrLyotgRSyBZ8CIOzR1crPRcCmste8+cNou2rDAtCdyQLLktTVznPJgtPF29jj3fCW/CMJHxmFLJ0yaDlfS0dUeVeAXBJZO0w2RAU62C76Jk4mEyCPFFsJ1wIY+ILnOdx61NTLR80yx+y8h7xlwBq4X7S9sKWqd6srs5a2i8tI7xoMyyPSLVc9R0DjOKQ4+jSfKvs4MEgOPJs1v0NOOoEzmzGRIMoGIwWk8hvZ0s7Nxsyz77jewiq/3b7JyzfLL8dbznjNocS1ypnV79z/6K/2zQa9FJYoETP1NgZITlT/Vv1ZzFnpUjJJpz0cN2wuois8J/EeJw33Bkf/sepx3LrX98t6yrnKW7+oudXEAb1Isp+zea3LpQ6rja4/sKPQ4/e3EqEnYTPUQ/hCoDjQOqY0Xi2iOiRFaDhPOW1GKz8+OI40bB5kBsL/D+ve0TLIzcHasxq41sPJwfW/E8xAzCbFCcYUxjDAdsb30CbZ6+YI+oMMzBxNLaI2PEDjUcJYvFfdVVFZC1ThRXY+Zju3NUky2y95H2ELeQc9+VjiMteC0lTJmsmmxwy9cryzw1a3BK+BsPCnU6JGpZelPaiuyqrzuBBLJeg1N0hHSYs9JD+qNH0p+jVxRPY6Nz68TfhL20NsPZwk2QkE+3bpKs7LxJ2/lrV0uYjFCsRhwPbIoMpOvYi6s77LuXK8b8ao02HjSPgEDvsf8S0fPO1Ii1aqWElWC1W3Wd1Vn0kdRftCU0L/PLI32CRcDeMFafY14fPRss+2yQvIasePwAi9WcG0t2WrD6kCoquXq5e5nE+eJL3k7AIMpyTTNutKRkvJPnU6czPcKJ8wMkQqRuxEpVUOWz5RdkMeL/QQ6/rM69DR4cOywLK6YbtlxHDJl8NJxU7Iobl0r12ycLADscm4sctM3rXzygu/II8uLTxHSdZVpVQzU7FSu1gZWQRVM06bT+tQdkdoPb0slxLMAwf3XeVR0pzQIs+Eyr3Jwsbcv5q/sbfIqqOjn54JlAmOkpMPlUinWNjJ/jkctjEFRDdMekHSMX4y7ig4KOQ7bFFoTehUnGa3Y9FMgD7FIaUDRO8K3hLJj8RVwtrDM8Zaz0DMWsVlxGG7F6gWpH2nUqkRq9u8qde6698BxBndJ40xkj1RS75OGUsaThBYgl/MXrhYJlseXCtUWEbyNpMeogiO/e/w5t5O1sjXf9YX0GrMSsiKwhq3Aa78pWSe6JSujceNro4qliGtHuDl/1ceuzAYQotCWTW7KpIuriTnJ9NAHlcCUgNg8HA2aFlOfjyuH2gAxumG3FHNItBDzkzPntI82MvOCMfPvtqu+ZuOnqOjn6MqqgXC9txg738D1RSKIFwrnzQ0QptFokXJTiteKGf4YJ5fqGV0X1pS0ka+NqobnAw1A+bzmeSz4cfe/dzK1V7PmcpaxTm0LayapmidnpW7j+KOl5Cxk2uiqc2N8G8LQycvNSk5XDUGKXUlTyXwJXw10VIBXhlfsm+Cc1hZdj2bKw4OWe/l5d/f2tsN2kzaAttk27/VJsqtvdav+50cnPKfRqCDqZ27c9Q26rT5dgbpFSoiUScGNFI/DUKGSQJYqGXMY0Nf6GOsY3dVm0nJPxMqJRUODq3/uO/b6Xjm9eLK39DWAdKNzC+9Na8OqmuiWZlCknaOxJEDkp6VIrHO2bj07BG/JeEruixZJbYeDyHHHpcnF0PYXORftWbidaRqlkwXObEkSgSH71rukukD6G7ldeVZ5Q7i0NaeyJe5baW0mZef+Z97pf2zBsq34KPu7fgMAiMOPRL6G7ktYDVhPgJNVV7BabdjFWDEZV1ckEpnRGM6nyCNFwAUjgLx97L3n+8Q6lPkJdpD0yLL77gury+tO6aemwSWfZg2mRaVT5nIr7nTb+mCCBkTfxccHgoekxlbHfQfASs/QaNc8Vt7XhpsoGb+SKo5RCsHDuT6Gv7n+yT1yOxS8Entg+Wc2lDPRL33qGKmn6lDpcaspLsly2zeWOvA8iX55gXKCyQSeR9TKTEyaD5nU/lfHlxBXJ1gFFfsSXhE7jaJIiAdnBV3CdYD9P3N+ZP23+5m4s3aRc+PvyS4nbGqrIml45x3oO2iqJsTmVilLMa93cv2+gcqCRMSbhdMEMMPDxdeI1AzglBNW/tW+1xWYXxO5zadLT8eDAf3BjgKpgce+Wv5YvzU71HiuNqBynO2VLCPseev2bVfwyPOnNqQ5iPtQu1989z8bQM1DlYg0SlmMZhEyVMTU5NQsFM8UCNGeEBXOJ8qLCCGHC8W1BB+CXwHjf+N9Zfru+Be1ITKpsJqvQO6sbfJrbCpca6ypgOcCZ6zqn3F1NrU8/v9DgTYD78REgjrDUsXdSGQLOtF7lBVSidQGlj2RTc0szGfIUQMtAzbECAJ5v0SAx4BpvSU62bhWdHawgi9S72Bu5/CJcuV0MraQ+a361XrHPEq+yj/Cwj8GXYfdyhIOXZHzERxRbNKw0ctPaY6jzIdJmccZh24FWgQ0RDGC4cBafzm89/ja9vg08HIjcPrw4W/hLZCtR63a618pFilsqs5vnbUieea9hP6WAT2CHcEmAepEgsdaSPFNehFBEBsQmdJNEKvMjsu/SZ6FEIUnhcCEaEJdAgFB5r7SPME7OTdEtIpylHI78dRzVjSfdUF28TiDudL5XnkGO0v9CwBARLPHZUkTjEvP/k7szaoPAs88jG0MPUxqCdkH5ghbR2IFNwUNhH6Al/7Kfjk65ThP90W143SEtKZ0JjHJsC0vae28qoTqJSp0admvsLb2usp+F78qQOrBdD/tQXGDOIRjBmvLZ09ATrWO2ZFvUHLMXkqCiNFFaoRBRJNFPIOpwuVDPIEvP1g9DDkcduhzvXJsdBv1Q3Vjdv84vToEuxi6Fjmfu0x8SX52gcXESYZ4CdCM402NzTzNE4xrCzsJgUluB8NGkga3xq2GBEZsxIMB7sCsPpx6wnkhuG/2vjZ29rm2lrUVss7ySvC/LTxsMGvEaeMsB3SUOMq8l3+8AHVBaUEaP2K/28G/Q05F0cs2TKzMa051z/4N8QocyMZHXIRGxC4FXAUJA2MDzEPXwhPAcfy+Ohy32bTR9b12M/YIeAH5z7pcu6Z7nDnl+vG7+vxEfyfB+QOLRk8IsAogSkqKEsllSR/Ib0dIB0AGUsXghi+F0AXGxWmDKcF6P/i82DqTejj46LhP+Ij4l3gvtYw0EDNDcUbu1C7frVdrQS+Ldme5+T1O/1dATsFBf7v9YX8/gFtBAgSrycOLQotzzYBO10vZyDkHYYX+gw3EFIXnBXPEu4TXxJyDFcATvWq7ozi79cq3e3f0eP+6pPtde8v9DDu7udo6eLqBu6i+kgG+Q02F5Ad9iHEIkYdiBmhGD0XvBXUFSwV5hTRFc0VhhdjElEIxQJf+5TwNeuA6sbpsek66eXqWulC3uHWudQcyfTAUsEavNy2t8II3D/sl/Y9/s4AYQDK+CHwjfWm+ff+Vgs7HjYqhyqRMKY07SlBG/AVvxH7CrQMoRTuGOgX2xWxFWsRfgSH+RzyWOfn3bri4Oe57enzg/Xa9bX4sPCP6PTk6+b36rP15gFPDDgUwBnIHH8c8RQwEMEOCg8AD8MPBRKpEpYU/xSFFLwPuAYpACj55PHd7PTtZvCQ8e/we/EM76nmnd6k2Q3Ql8hTxUTCKr9axqbbFvAb+K/8lvzB+7v0oOm67Onzr/xYCIkYxyirKH4oMiuWIyMUMg22DhAMBgs7FCEcvBrkFysXWBNSB5D7dfRD7FblwOjb7qX1pftJ/Hz5xvnI8X7nrOKn41foV/LJ/78LOBPdFw8XRBYzEFgJCQe6CLgLqQ2ZEDgTFBWTFN0SIA0ZBJP7GPdi8f/tifAA9rH5ffiM91f3fu0/447aztSGzXHMzMyhyZbJG9XD6DfzVvmW/Dj8rflW71TnS+8z+BgAiwpEIGIn/iDtJMQixxT8CRsLkgvtBnENyBiRHAAZOBjRFfAMkgEh+dbxO+1m7FHxDvfw/d7/Iv1w+3n4su2V5RLhEOX560n3wAUzEKgTQRXLFHAPfQUSBHwCsAMtCi0PZBEXFbMXLhPnDv0H//x39s3zPPH378T22P3K/eD8H/0m+BztwONp3YPWFtEG1LLU49OR0dfWG+ml8Wf1NP3W+tTzUu/B58bqgvY9AmUKqBiMI4UeWhqFGZ8RoAZIB8MKLghdCxIYBSDpGvcVABTFDQAEYvt49ZnzbPJE9fD+lQG4AfABkv0H98Lvs+eX4qXmi+4H90wF1g6gED4QMBD5CS0Ai/2c/hgA/gY/D+sSGhGiEgkRVwonAzD9fvaQ9bT0TfZi+1YBrQKHAYf9p/ii8HTmkt+F3WTbzdoS3Z7c09bv1tvkkPHP8Wf5rflR9s/xHumZ6ZXzwv/1BHAOWx03GgURuhPAD3AEWANQChgKdAhfE60cZBsjE5gREBB5B/f+Hfo5+nz5ovoaAmMDkQJtAzQA8vqj9KXsuufK6XvwZvacAo0NqA+tDGkKgwcv/8X6O/zG/pAESAw+ELMNqQ3JDIsGAgFY++T2vfcJ+Qn5nvszAiAE2AGO/kb7g/WC62/kFeIL4mzjmePI4ureFNkm3m/uA/Jw9zn66fh59FTss+fJ79L8NgLLBHAT5BdHDR4M8g1MBSH/DQZiChoHXA2sF4AaPRKFD00OgQrYBXz+NPxO/wj/ZAGPBYgF7gT9AqP+0PmW8qzr6en+79P1Df2kCjMRLg2iCEgHVf8i+MX6FP32/w4KWhBYDREK4gtBBm8BRf0f+Of2MfwU/cj7FACBBegD2v8Y/bf67vL+6g7oYucy5hLnGOg+5IHet9vP4p/vmvIP+nH6/PeR9DDp5+dX8ub9QP/IA4wTUhFxCAkMfQo6ASH/3wWzCMMFFQ8cGEoYRRA6EFQOaQqnBv7+S/7sAosBFQUTB/MHigfkAwMA/vkH8hnsOu5q9RH3UwGeDs8O4QgiBvYCafur98/6Df30AQYLsw7SCfMHDwhPArv+yPpJ9275Pf7n/Ar9HQOcBnEDS//u/Nv4W/GD6q3qv+lb5+roeekY4x/e1uEo78PzvfaY+dT4qvNb7Lrneu02+sz/8QCqC7UQDgniBrgHjwBp+wUCyQeZBsoLOhXuGA4TxQ1rDF4KnwcrAyT/KwPVBXIHIwlYCUYJYQajAfX8qfXG7xfvWfX3+Vz/4wqAEI4LFQXFAoH8+Pfl+Xr8rf/CBwMP9wyqBxsGugOO/jH74/eS+BH9QP/b/Q0ACgUABNUAyv0v+pX0E/AC7qLriurX6o7qB+hv3wPeAuqp9Uv1uPia+zH23u+951vnjPKc/sz/aAVUD10MegWEBrwB0PmI/GsG6Af3Br8RuhhPFgAPWQwOCqwJ/gYh/3kBNgcBCKMLtQscCW0I9AW+/3X5+/Lb7/TzAvkj/A0GOA+PD6oGJQKY/m/4bPez+5z+LgPbDAkR5AmnBjEEBf90+wX5DveC+4EA6P8KAH8D/AQWA27/FfuK9S/v7e4v7/Tuee5d7+DscuVF3oLcg+p39lz1BfnW+3v2LvF+6H3pbvWx/QX+SQUWDUoI1QXRBR3/f/rM/6kIMgh1B6MQZBZNEwAORAzdCbgLzAgy/wQECgq3CHMKbAogCM8IMwczAUT6ffMO8pX5W/yD/j8JqA6OC+ED8/9k/ab6h/kq/ED/JgXNDJwMhwbTA+//A/yM+635Uvmj/tUA3Pzb/iQDrgFc/+f8g/ml9dPw5PBz8lLv2eyF7O7n9N/62xzoS/k6+ab5jv5I+S/wTeeZ4w/wz/ux/SoE2Q7UDH0FDgVL/xz2uPiCBCEHjwXeDCUWyBdLEV0LOQhpCXEIIf/X/4YI6wkJDNYNiwoOCpcJfgSI/HbzoO6w9TT98/68BR8PVhHPCDABzf2E+D/3PPvN/doCNgwdEhAMcwVMABX7RPpq+gP3PfqWAIsADP+eAycEQP9X/Az51vUV8j/xCvIl87jvP+xt7BjouuEp36Pq//cY9x75gP0d9UfwFedq5mP1sf3X/nYFOgzKBl0BogJC/Qr4YP9BBg8Ijgc1DfwTYhMODn4JSAeSC4wJcwB4A+QJfgkFDEoNhQlGCr4IuAHW+8L0k/IA/PsAoAEWCDwOawz1BJ/+aft1+ff5zf2rAGgFdgtWCzsF3wGn/c35W/s8+9/4iPwwAAL+Fv9rAVz/hfxV+in4nvYl843wk/He7+Dsd+yE6Enjf+Fr6sP4dvj19sr9gfck8FDoReRt8YD9iAALA9oI8gnPA9UAV/399VL5qARYCKcFrgoAE0YUZQ/hCO4EwQi1CukBCgBrBwoKlw3IDkYKtwjhCL0Ev/359fLxqvgwARwEoAaDDKgPWwn9/937v/hk+cL+RQHvA6EJqQ3TCLADWf73+On46/pP+fD5S/4W/x7+LQDw/uf71/mO+Hf2TfF176bv9+7q7Qjrj+iE5GTgeOtU+0326fRe/Dz2yPEG6ZrifvHQ/hcBpgL3BusJ/QM0AC39uvWT9ykGpwtGBBkIbRIOFPAQfgmLAU4IEAw9AqL/qgYACR8P/w8ECS4IRgl6BYr/3fVU8f75XANFBdUFswnyDhwK6P/V/G75sfi7/kECFgMECIAMMgjBA27+4/dr+SP8L/nG+Rj81fxg/hEAOv6Q+4r5G/ia9pfxRu3D7tztru7S7Jvmh+Qr4Szv6f1G8Xv2ofxE9GzynuZB5JXzqwB5AhQAWgWCCKkC/f8H/Hn0Xfi+CPcLrgFyB/cR+RKTD7cIpAC2CfoMawE7AP8F7wftEKgPYwiqB4IJvAYmADH2s/GY+okEqwVvBVgImg8qCtUADP6c+EH5/f9KA5gCygZkC3kHdwRr/tz3xfqr/D36bvlE+vL7S/7l/uf8yfnp+EH5gfd78IHtku6A7m/uxukV53PjKuLd8aD9qfBG91/7oPPy8aLmIuQe9MYBzgBo/e4EogiYAiz+bPyw9Sz4RglyC4gAFAaxECsSsg8VCR4CgAsVDl4AOwBKBNoH6REKDw4JrwnRCpUHNwDS92ny8/knBF0GngRrB2QQjgsJAYD+a/lB+RgA0wJSAgIGZQr3BgAFCP9P+Bz8TfwB+l34UPeK+oD9g/4f/Tj8vvri+QP4Xe8x7Jfsbev37uTrUOiD5b/lL/UO/BfvXvf++NnyBPEU6YrlT/QSA1oB7vsjBIoH5gBT/b37n/S594IJhwszAXMFSBCfEXcO/QcuAyMK1AzNAWsBQAOsCFgT8Q9DCcQJTAsdCPP/UvmO9F/7xwXoByMFpwY0D6oLLAFL/hL7Dvu7/6ICAQPcBdoIhAbrBDb+1Ple/Mj7Z/kz+Qf3kfla/bj+ofx/+nj6DPqo9tfvSuwt7WnsFe1N7GPmcOKc6m7/tve17r38nvbB8EXureW56GL3sQew/zL6AARpCiH+kflA+n/1u/pBDD0Hkf/tBggSIxNkDAAECQbgDjUI0P+cAiIByQweFrgMCgoQCysNzwmo/Av2x/cNAEIFlQdsBQIH0RDbC+IBx/x1+hr/KQFj//YCBQcaB+gHSAYq/Nb6nP5s/Hz5APZg9Xv7y/w7/NH9a/kc+0v+GfaC7BDuieut6q/s9+kS5vDkuvAyCF3zcu9Z/o31Kuxr6n7nUexP+awJwACB/AcE5Amt/4X23fUA9mP/sQsuBCkAsgqaFJASygqZBUUFRw2MBDb/YwMpAb8QDBfJDNQLVwrIDX8I6/vE8r33NwaJBJ4E/gaTCXURiApDA4D+mPkM/pkAOf/wAfsGswg7ChoHzvz5+7f/xfpJ91n01vVT/Vr9y/y7/lv8pPzW++T19O3B6xDqSuzp7lPpT+UH6LX4nAe476vyEP4k9UXpweZ37FHxcvhrBocB8/8gA0UFnP6Z+BP1XPVyAu0L8/9FAKMM8hNkETkIzwllCokIOwCSAesEhwFPEHIVIw56D4QLEg5kBsz6OPZO+qAG9gNyAQUHSAsxD0oIRgRgAiL9AwAI/5P8WAOEBR4HewjYBpcDYQGLAET6HPdh81v23Pwn+//8sgDN/nX/0f2e9m3w2+946yfri+7I63nlCOZO9Y8KVfVh7o4BQ/su69/jGeeU8Cb33wAz/r8BlgVFBob/I/dE9Wr1Av7cCmD+Y/oYCv8USxHQB6AK8g5gDBcBEP6zBEEBrwnyEioOpRO0EQoPVgsGACz4tPq6A0oDbv+aBKcKBRGVCwIGCQZBAU8BkgEg++L+lwQLBKAFbwZhBukGJAMm/WL30/Vw9mD5afev93j/YQFdAfP/nffT9R31+O1W6v3rAO2x6YTkJ+ubA9oDVu8K/Y4BuvGP6CvmSuwv73z69v/i/dcHPQeOAjz7J/aC9gD3TAZrAsj1eQHqD7oTAgzmBhUO9BBACBH9UwF9AdoCAA+qC9EPtxc5EoEPEweu/TH8AADdA4D+YQHkCMgNqA9pCjkIVwUyA8sEWf7P++YBbwBZAjAGTAazCcMG+wG9/PX3q/fL9ij16fR7+z4BKP+4AfD9Jfl1+Z3yse777Rzs7+us58zmpO28BnYBafIlAV4AQfMe6rDmEuzf7VL64v0M/zEJzQZE/7r7zPrc94z3hwKe+yb4rwRKCCoOGgxRCCIQRBFBB+z/lQKm/iIAUApRCE8RMheVEV0QVAlWAqsAzgBhAWv+KALSCU8MHgvfCnoKSgjMCMgIAwCS/UgBqv4h/m8BiAWEClIHugNoAcT8BPs89h/ybvXB+9v9ZP3o//r+I/zB++72DvIx8l/wKux357rmge2HASkA+PLJAq4Gn/mP7X7oLO6J7MH1+fsX+XAE9AbX//X8u/p4+kf6JgDn+xz3zf7tARsGxgbvA/0NGhL7C98F7wNg//j8rAQ0BegItRAwEEMT0w0eB2UFawKQBAcEZAIMB6MH9ggDCh0I1wenCyMOewgIA+QD3v8V/BT9XgDyBK8EMQXNBsUCav9O+mn24Pf3+V78r/sx+2f+Pv04/Ef6BPYj9xD5zfQ87D/skOwm8mEBAPbr9UQHSgR9+PTunfJd9HnuS/lu+tX3FAATAkP7Bfqv+zH7jPxPAVT7C/s6/qH7hAAa/zQA5wmeCfYIEgkjBR8A2AAIAz0CBwmpCFgJjhCeCUUGXQdTBUcIYwjCB7cIZwckCCAJCwRJBXILvwzSCXQJmAewAxABZQBIAXkB6gCvBPQFVgFsAED/yPvn/HX+UP3A/Iv93/0D/In75vg6+B/8HPuJ9qb0t/UM9FbzDvxc+l/2fQFrARP5nffv9Y/3ivQp+Mr41Pif/gT7zvez+5n4h/kd+mX87/qd/Fr9//cK/en+BPtyAYkDVQMjBcEDtQE3AYAC0AL0BUEH1QWSCl8IbwW0B28GkgZYCFsJMQrsBxIJkAmjBsQE1ggmCnQI0wiCCBMHQgX9A20DPQI5AxwEPwQ9Aq0CGgKR/rj+hAAh/ykANADtANv+jv6t/tL81vvg/FD83ftg+Zj5mPmQ9gr8f/+4+Sb9BQL8/I74F/mK+db1Kvdu+hT4kfqY+kX4WfrU+Wn3fvfv+ob6cvlH+p33QPot/RP6r/wpANf/sgAoApkA2P12AN4CvACwAsgEkgVdBgcFiQQxBWgFwwagBp8HeAiRB+gHpgcVBZIGzAjNBzUIwQiGCPAG3QTPBMgE1gRiBBwEoAXgBG0DbgJdAlICgwJ7A8gDQwRfAyECCQJ9AWD/MABlALT/AADQ/mH9Hv7J+Sj5BAOD/334UwGzA5H69/kx/BP59faC+4f5vfdg+or5RfgX+Sb3rPaO+JT64vge+ZL4APei+kv6rPZG+yz+d/zR/bT/gP40/K3/mQDz/u0AcgLaAskCPQK/AfABzwOZBRwFDQbmBnYGQAhMBYIDowbmBvsG/ga4B8EIcgauBjMGpwW4BhQGKQbmBVMFygVFBTUEngTfBocGkgVgB9EFoQRvBVEDogLIA2QCuAFjAy8Cyf9QAHYAUP31/Cj/8AFQ/Z/+BQKZ/XD7Qv0n+y/5nPkA+//37fhj+tX3H/d+9134RPmT96f4SPlI+O72q/e4+KT3Qfh6/KX7kfr+/Z/+A/w0/DP+KP4Q/jABwv/6/78B3ACkAI4BAgLkA4IEHASIBe0GGwbWAxgFjgfKBSgHCAiOBt4HQQdrBk8GqgYuCL8GIQetB9QHWQfqBQYGjgZnB+UHnwdSBy8HMwfjBT8EkwQcBVQEhgMcBIIDDALbAWgAL/+x/mr/PgDfAS/+Uv9rAb/9WPsm/S77lflc+hX7yvij+ff4wfb197z4FPjc94T40fjx95r30vYc99T4T/ig+JH6EvsS+yb8Jvwn+/X7Gv6E/eb9OwBk/rT+fQERAGf/vAFuAocCkwTEBIIEJQZBBncEbAWfB4AG8QV1B9gGFwf0BmAHbgfJB9QHowdcCIMHLwdyB44GGwYeB7cILAdkB1wIyga4BtgG7gT5BH0FswTyA6wEKwOwAukBZQAwAKAAFv+t/hcBKQFk/fP/FADV/Hr8ufyD+pj5RPoh+kX4v/hh+Ln3v/i8+Kj36vda+EH4//e296j23PcJ+bn35vgH+9P60/pb/Kv84PvZ/NT9Xv1n/or/1P76/2sB2ACkAMMBhwLMA6EEWAQABSIG8QV+BNwFgAarBVYGEwftBk8HEwe1BkQHqgczB5EHvwc6BygH1AY6BpkGEAeVBgUHowduB4cGcgaLBS0F+QR+BEMEbQTMA+gCawJvAYsAPgCb/3z+h/6kAMMATP1n/wYAnfwf/Gz8ivqx+S/6gPk++B75BviI9+34GPgi+JL4ffj0+Jn4A/gj90X4Hvlv+FL5tPpp+yf7nfxM/XP8Jv0o/h7+cf/a/x3/MAB9AVAAegDfAVYCUQM/BAcEywTjBWwFIAQxBT4GVwWIBYsGsQb0BTcG4gaZBiEHKAfYBk8HowaLBloGwAV9BeoFLAaLBvAGBQeEBTMGiAV3BEYEBwTTA4YDogPFAmQB+wBzAMb+tP7p/iH+xf9TAKD9rf5S/378/Ps4/D36M/kF+vv4gPjY+Mf30vft+JL4ffgT+ff4/vgM+ar4/Pdo+ID5Ovmt+TH79fvP+zf96f0N/Zz9u/7N/v3/3v9H/6cA7QD9/48ARQG/AXQDIwTrA2wFzgWTBFQEKgU7BfkEbwXDBeMFuQUGBkEGSAZoBt8GzQa1Bl0GEAZaBQMFIwVMBSYF6gWEBrwFMQVlBdIEJwS+AwgDwQMLA1YBxgEbAab/qv4J/sP9Xv3j/AAAwv/L/Jz+1P7B+1j78voo+Qz57PlW+PH3hPik9zr4ffhI+Hz5SPlS+QX6lfk++Gj4VvmO+b/5Z/qs+738r/xB/j3+lf2x/pT/xf9XAA0AOwBTAWgAwv9MAbUBLwLEBOsDDgT/BWgFdAQxBKgEMQVeBQcFvAVkBuQEYQWqBgkGMwaVBpwGRQbABS0FmgR3BKUE5wS6BJ0FDQbyBIkEdwTTA38DtAJrAnwCdgHOAGUAR//U/aD92fye++77W/wW/9v9ofvK/eb9n/qi+q35ffij+N/4H/fn99L31vbZ92T4jvgX+UT5/vmU+iH68Pg9+Q/6ivoO++v6fvzD/UH+Y//w/gH/RQAXAfcBTAE6AbEBxgHOAJ0AkgEXAt0DJgW2BEgGKQbcBa4FFQWzBEkF7QVeBdUFoAXdBPsFTwYCBk8GtQYFB08G2AUfBQAEGQTBA9MDOASQBK8EIASbAzIDnwLfAT4B6gDqAHX//v3m/dz8vvpE+dT5BflL+Tr+svxH+lf9G/2R+Vb5ZPhp9x/4Kvew9bb3HPcH9nr3Kfjf+Db6BPu2+wf82ftA+mD6HPvg+wf8xPxy/jb/vACVAW8A2wHlApADEgSJA74DBAMvAtwATwHJAg8D2QQpBk8HowfiBtQGrgbVBYwEUwWZBqsFUAUxBdIEcwXHBa4FTwYlB78GbAWhBA4E7AIaAlYCtwI1A8UDNQPeAocCnAEKANwApACO/Qn+nP6v+/742/gb+M/1FvWO+J38L/rC+S39wPz3+DP4evfL9xj4P/bI9Z72ZvZU9pD20veY+aX7Cv3f/fP+0f3j/En86vwQ/mv93v6uAHkBsALMAqwDOATDBVkHTAZ2Bm8G8gTJAm8BbgKRAugDCQY6B/oHHQh4CFgI9AYNBqcFZAY6BlMFBwUOBDUEwQSCBDQFiwbpBo4GTAX2A9oCQQIJAd7/PgGVAb8BFwGLAKAAHf82/jP+cv5C/SP7wvoi+E71UvTd8e/wRvcB+j/2D/re/rT6KfjK+Kj3kvh5+Dj2pfYD9xn2z/XI9o74u/le/VcAvwHhAiECSQAiAF0BCgBq/8ICWAOJBAcEWwRoBhMHcAkVCokJOAqFCT0HhgOiAukBrgEEBMMFMwemB1UIRglfCNQGNwY9By8H+wU7BbAD5QJcA1kCDAIuBJkFuAZBBjgEkANgAu//jv5q/2D/0P6U/6P+DP6O/SP8Ffw//G37g/kT+br2o/PI8ZPtw+1k+O/1APLP+0IAcvmc+HH6T/m7+hP65/YK+Fn5yPZt9un4M/mh+xsBNQNyBnsIPgbWBG8GwAVrAiAEOAWABgIHggRSB2QHJwnwC4QL8AtTCzcLcQjLBFkCNwBIAgwCyANsBcgEawY4CToHUQSLBncJeQZhBYkEVQNKA6ABGwCgAYcCiQTKBYgFMQSbAwcE9v9n/kkABf9k/uf84/wx+635xvlP+GL3H/cf+Bz2JvJV8K/sN+7F9bPxbfGp+s78rvhE+Zj6ovqW/GX8QPr2+jT8Afpg+rb82fv0/dMC3wUcCmQLqAkVCgIM7glPB1gI4QcLCXQI5gZSB+YFmQoNC0kK2QnyCR4LRwgYBdgBGAAGAVcAvAE6AXYBcAQ3Bg4F8wLABWYI4gbfBsQEggTIBGoDLAIpAWACdwTWBNUF4QNpBOAEhwEpASkA0/9S/1D9Ffw5+ln56/Ya9Xz1L/QV8SHvpO246U7rDPWe8ZzuvPhi/NX36vf3+Yr5ff1d/or5GfvT/4j82fwpAJ0AfwPJB88JAQ3OD2YOiQ0UEAcORQuVC28LwwpGCQcJ3Qg6BxsLygoYCh0IfAdyB+AETwJS/9j90f28/aP+ff02/mEB7wJgAiwCWAS/BkUGlgXMA8sECgWsBBIE2gL8BDcGFwY6BikGhwYbBvID0wKAAhcCiv/0/er8Tfvt+Nr1JfTN8zbwsOv36TznL+Ua6yXztO9U8dv5pfvE96P4Uvli/Nf/gP7v+kn9vv/z/m7/FwIOBTgJlw33EC4TGBSsEgsTQBIfDxINdA2ODEEL1ggLCP4G8AaiCCMJ8AY4BQMFpQMM/8j74vgq98T3/vhk+PT4cv2b/9r/KQEPAzMGewiQCJ8HTwc1CNcHSAfVBUEGIAjrCRUK3QmyCs4KYgmKB98FrARjA8YBu/6a/Er7qPdL9H7yZ+8q7Lno7eTB4eThhOgj8QLu5u7s+br72faj+KL63PxuAr8B5v0T/ooCJQKKAvEFHQj6DNwUoxZVF8sY3ReCFwUWTxBUDhwPXw2SCtAH5wSAAXwC+QQBA3IBaADfAN7/t/oH9mzyuvHu8mLy+/KR9MP4kv1A/+j/dAMACcENtg57DqUNyA0jD8YMQwjoCB4MsQxjDW0NWA26DY0NAgtxCF0HBQenBT0CNP0h+mL2z/CI7Wjp6eTq43TiDt2L2nzgBOzA7anrwfUD/db6ovqI/Df9bQOrBScDAgG5BR4HHQhYDUYPKRAjGLodJx3THDwdqhsfGnAUdA5dDPEKuAfuBPsBcPzF+j3+Vv5p+yX5T/kr+s/2RvH17CrsQu0m7Rzt4u8z9F35YP9yAkMEHwpcEjMWpxWVFWQWARcoFpwRjA7jD2sQjw+ID6gPlg8NEKgOnAuoCfIIWQfFA3X+yfl/9dfvBevI5pThft0Z3PTZf9ZV0unVY+sM7xXosPX9A/D+mQCHAoIDTwczERcMtQVLDDMQHQ0FFgIW2hJuHNcmUSIaIIsfhx/WHOATYgkcBS4E8QDq/MD3MvDy8S33g/UJ8/XxyfQx9wn08e1r6XXq1OqS6X/rz+zL8jj8qARdBkMJTBBdGgAdPRwVHnYfnR4qHaoWVRKxEXQSTxCaDwAPyw5XD6sPGwt0CKMHOAVsAG37e/YZ8S7rPObX4O3aONje1kPYg9bk0rPSNtv77fjyVO06/koNBAk4CfcLuAwnE84Z5BK0DPUTmxdPFmEaZxftFXIgBSUNH/QasRqJHf4Wdwmc/h36yPqk92PwVukg59brZuyj6YTp3urR7k3xle9w7ODsWPDP8V/xLPNG9wH/TAsZE3IVvRkvIAcosyd8JqwnFyWvIj8e0RXEDuYKpwq6CJcEogLdA2sG9AV2AXj/Bf9o/UX4wfCe61vnoN+u2eXROsuNzCLPLs7ZzkDXauu2/BL7ewSjFh8fJBw4GckbZCCRIXsd+hE3EK8T6g8CEV8SIBOoGXMehR4mGRwTaxWxER8FQfhn77zugOoq4ine+tvE3QjhvubQ6rHuf/XJ+bv5Ofp39/L2TfuY/mT+F/5cA5sNBhXPGEccPSGtKtwtfizLLEUp3iVhH1sULAtwBOkBZ//C+qP44Pc8+zD90/rI+pr8cv26+6n1nO+x6gDj6Nur09fMfsl9ys7Ob9Du02vgO/czByAJyhWIKa8tOioKKWkoZicOIxEaMQ/+DOoKSQV8B7MJnggSDfsU0BYyElQOsg9FC0kARfOH6YLmkeAC2qXXydZY2C3e1OXE7KHy6PoJAjYHngi0B0QHRQspCzUJWQeNCIEPPRahGc0bSyHVKD0rtyvFK0YnJyKtG5gRdgYf/Zb3r/L/7dTq9OlQ7d3xKPSa9ij6/Psm/HX5tPT77cnl/94A2EjQuMvhzObP5dGl1w7sXQeqC+AUkyztOMA3VTYUNH8xJSpSIeoPsAPbAf/38fJD9qrzQPUMAvALpgy6CQAPvRPCDEgBqvN67fDqieEm2VfUYtNp2OjgZubd7DT3CwQVD/QUrBdrFgsdHSGcG10R9g0zETkSixDzDKUNSxYPHN8aOhvBHKUdYxyEFQYLMwGj/Rf5YO/158rk1OVI6eXq+up178z1HfrD+KX2L/S47jXrvuYi337YM9YA2HfYJdoF8GgAKwOkFBIsUjDgMuA3bjo5NXUwrSV2EEQMQAMY8tfqN+la5CnpePDj97D63AAzDOsOTAtvBtUA1/95+GTuAeZB37fbON1H3E/fBOdc8Kz73wYNEAkWdx3dJ2AqkSUvISUgjx64GuES3Ar/Co0Nqwr+BokJoAsVD/gPzQu8Bp0FfQVO//X3P/FW7rzusu3O6ADnXeri7kHv6+zy7D/taeyw6y3oHuTo4Tji0ODn4iv1lvzA/MENSR/OHlMkASspLncymjLQJqAavRlRDqP+W/cX76jnfu2A7nrt1O+N9X///QK+/+z+8AGIBWgBcvkh9I7vRuz85/bg9eL555fsafJ5+an/xgbKEDcaWh+MIsoktCYYKLElcx6zF0sWLhPDCyUG3wUxBDgE4QPe/3P8+v5TAWf+r/u0+Rr6xvkm+LLyrPAZ8UrxBe9Z6nfnyOYo5aXi+98Y3hrgLuFd4Jnj8PSnAR4CQQz2HBohXiSCJ80pri5NLaYlpxpTFb4NNQMs+Jryyu067pHvYvIU8x709/3TA2gAtQCiAuQD9gNk/Rn2VvOf7/DpteO141HnK+sJ76DzqvlgAsQJoxHPGNkeCyIMJdcm2yUIIQ4dAxo3Fb0OvQmjB9gF5QLfAP7+/Pw+/VL+U/2P/Nz8sf22/D/7Rfj59SH1E/VK8S3tyeot6Gvk5eB33QLbFd1G3XHcj95R6xj8mP8/BCATjB6UIc4jASdzLsctyileI90XNhIMDBT90/X+827vIu6d8pnzX/Hm+KQANwA3AdkEnQW4BsgES/4d+v31Je9352vluOXW5h/oauuA73T2Wv3aAsMKxhYOHeIfzSSTJxYnuCQWIQQd0xd4EnsO9Qk+BU8BL/6P/IP6pvkh+QT75v11/hr+1P4v/+L9vfuY+hf5g/UK8tTugej14gPeHto42BLXzdXF1rjal+Zw9+n5WgFOEkMdWSHiJNcqczJgL/UswiYAGTMVcgzS/Jn4xvRI7nvsk/Hm87Dw8vYJAegCjwXACnAJmQrACt8F+v5M+MXwOuq65izkQ+Hf367kZeg/7N3xQfjFAz0SFRgoHOcijymRK6EoSyUqI8QeZRk8E5EMbge4AfT9z/qc+N32EfdO+tv9DP9L/30BCwQIA3kBTwEa/6j72feO8+TrN+T13WHZQdU10pzQb9AL017ZzeoX8yn4XQbGFT8dESS2KPYwmDQLMV0vAyNTGu0UkAjf/Tb5JfP66oDu6fOt7y/wWPsaAkkFSQq1C5wMdhB3D24HbwDd+sfyX+y95wviJ9y93dvf7OBd5OboOPIpAUEMYxJ+GUkj5SpiLW4rvyr4KHIleR+XF9gQzwiKAor+qvkv9EXzMvXR+HT7qPym/gQDHgcFB4sGoAZsBaMBbv7E9nrtD+bR3/XYJNLyzVXMmcsFzN7RX+H561Txav/YD4cakyP5J1kwejcINcgxPilFH/8ZnBEWAzj8t/VR7GvuUPIp7tztmva1AYgFtQZuDJMORhNPFegNEAZgAuf7+vRm6wLkkt4b2gnbNts72fPbLuaO89/9ZgS6DYgZfCXVLfUsTC7AMrAwISsaJdYcIxSQDZEHAf8V9g3zCfO48431g/Xk9jD9+QP7BR4G6wgNCz8JSAdFAXf3FfFA64Lhfti/0P7LFsiWxeLGFs1125riUewN/ToLTxZ8IXoorjPoOtY26zamMO4nmiJ8FgcKMwHP9n7xxPGh7Xjrz+tW9PD9qv2gAWYIjA/iFaETAhCJDd0IhAVG/OnvAetW5Jbe3dz21v3SBNdT3+7nEe2c9KIC1BBmHSElHyhuMKU2iTadM8MuuSlXI8YbeBITB4X8TPiz9dXyHu9W7ufxW/d6/F3+lgCuBmELjgvKCv8FOgL+/f31OO3I4hHZzNKUzMDFf8Idw67PoNWZ2jrp6/boAiESTxoBJh40tDXzOcc4tTPkMV4o8xuhEzUJ9v8Y/A/18++F7OLurfTt8+f32/3yA5sNyA5bDigRzg+sDd0Ijv4d+srzuuzT5uDdz9dg1jnX7doq3TXh6+uL+AMFwQ6HFTgi7iwRMuE1gjb5Npg1YDDEJ4UdShOjDPUEp/0V9kDwgO9E8OTwtvEX9Ir5n/+OAmgFgQXABfgF9AFC/Er2VO3h5YDf0dVtzb7HBccZzfHOE9EM26rlFfHl/hoHFRPBIoMq0jGmNZs2FTekM1stRCYTHK8U0g4RBaP+/Pe48yz0afLA8rv04/e7/0ECGAUHCusJ+QmICikGogO3/275AvSz7MXm2uGl3FzcIN2l3I3hXuht8Nr6nAJYDY0Xwx9hKbsvpDP1NnQ25zLHLuAnQCGoGAkQ/Qg7AEj5JPWT8eLvM+897xjygPS99+z5cfqo/C39nvuO+ff0t/AH7E/krN141yXVxdYu0yfT3Njd3NXjxOyI8mT9Owp7E40cPCLxKP8u+i88MTcu6iiXJzsjBRsKFNQMlwgABCH+4fro9cT2n/rN+PD55PtX/Cj/HwDz/s3+ef2n/Vv7ivW98TPuGutB6jXnp+Tl5a7oOu6k8mb2Cf5oBQsOGheiHOsi3CjZLBcvAy4TK14pgyX+H5MZwhFeClcF8QB++/31//Kv8ozymvIu8Z7wMfL48rLySvGH7lDtE+uw5tni9uCO4J3e4N2y3tzeNeEL5hrqZ+/H93z+OwW4C7oSZhgxHb4hbCS8JPMlQycKJMYfjB1yGi8WphFfDRkIpwWkBS8Cef7t/Rv95PuJ+w/6efkX+f746vdW9CPx0/C/70zuDu1O69Tqe+w672nxd/L89sf8ygGcB04NdRGCF88cnB/XIMkhoSOrI8Ihch+AG/4W7hNWEK4LXQfaA5kBov+Z/b76cPdb9vb1AvRN8WTuhuvY6STmLuEb3tLdB96U3GbcVN1X3kfhZOWS6IjtsfQE+7wASAb7C30QaRTEGUAcIRyaHsYgTB+9HdMcixrvF5wVzBIAD8ENJw4QCzwISAeuBZADPQJMAQoAAv56/H/6W/ac88Txse7B7Fzr/+gx6BDplerF62Lt6PBc9U76wv/5BKsKRRDZFJcYWRv8He0fgCCfIHkf0xwlGmcXFRSjEMkMaQkXB/UEfAJZ///8uvsd+hT4uvU387fw3+276rrm5+Jt4lHhq96I3ined90z3y7h6+K35mPrUfGD9ZX5wv9GBFUITQ6xEagTYxeOGs0b4hupHBUdAhuTGX4YQRUtFEIUvxERD7gMzgr5CFMGegULBB4BCgD0/Zv6LPjM9ZzzcPHG7kbtouvG6tbrB+w87BTukPBE9EX48vvmAHoFyAkuDkERaRRSF3MZXRu4G/AaRRqMGOUW4BTpES0P1wyECggIdwTmATAA1P2X+yz5zPWH89rw0e1Z6uTnMedP5WjjV+N74ljhieLy4rXj3eaR6kbtIfDK8+73sPqt/isD+wXPCFUNNxB5EfwTEBbJFvoWXBeYFrUVwhaRFnoUWBJgEa4PjQ37C0IKZgjGBjQFSAII/zf9FfvD+Lr2ivR38jXxz/BL8IDvZ+9/8CPyQfSF9tj49fut/+UCSQXUB8cKcQ2hD9ARyBLIElgTqBO6ErERtRBeD+gNuAxbCkgHXgUcBIAB8/5U/Hn5HPeY9Dzxtu2X7AHryuhQ6NLnWOZx5jXn4ebd55jq8uxP7rPwPfTh9aj3OPwz/nz/6AKOBnIHVAm7DCMOlw4NEEQR+w8XEZMTMhIhEUsRBRF3DzEO1g3wC48KSQqUCDsFvgNnArT/EP4O/NT5Pvhb98T2TvVW9M30DPW+9T/35/fC+aT8zf6LAC8CXwR9BkMIPwrDCywM8wzPDXsNLg0BDVkMjguWCroJhweLBaEEWAPtAKb+2fx/+mH4OPaE82Pwpu9v7m3sC+xm66bqiuoB6/7qDuzH7UvwJ/G28oP1y/Yf+M/7Cv06/qsAVQNpBIgFFgh+CdIJFwt8DNQL4gz1DlQO1g0ZDnAOXA09DJEMdgtGCkIK7wiEBhwFFQQCArIA/v7D/Wz8Rvu++mf5lfjN+NT4S/ni+VX68vu//c3+JgBaAdoCfgTfBZEHeAgLCRwKXgo0CmUKTQrPCV8JwQjNBxsGkwSwAxcCGAAz/nr8dfpr+Gn25vP98F/wgO+r7WztHO2C7H7sAO1J7fTtze8O8mvzn/QV96P4zfm9/Bf+zf6SAN4C5AOlBIcGXQfvB8UIrAmMCd0J3wviC5wLAgwJDHIL/wprC64KAAqoCf0IowcwBosFAAQLAyUC3wCi/4f+Gv5k/YH8H/zr+937Ffx6/AP99P2c/oP/XgACAQkCHQNmBEIF5gU+Bo4G8AZLB24HEwfRBocGvAV3BDkDSwIGAX//jv2a+475bPdn9T7zQvK68HzvPe997tXtG+6A7qDuBfAV8m/zn/Sz9tH49/lD+679SP5c/0gB1wIWA/YDQgWIBaAFdgYMB8MG6AdRCfYIswhDCZMJjAmQCboJdAlwCboJ7wjCBxcHhAaBBe4EGQQWA10CnAH0AMz/D/+m/i/+S/58/kv+YP5O/8z/0P9JAOoAqgFkApQDTQQ8BLMEIwU0BfwEaAVlBecE4ASTBHgDLAKEAY8AE/+S/Tj8lPrp+B/3L/XY86HyUfHv8FXwpu9u7/Pvv++C8DvyWvM69N31Jvim+ZH67vwo/vr+lgByAt4CeAMOBbwFwAV5BgUH/gZuB6wIlwgBCHEI8gjICKUIjQguCFEImwjXBwUHVgYiBm8F6wRfBDkD7wKtAvsBMwHHAKAALQAmADQABgDe/9UATwH4ABQBvAEzApgCNQPTA6wD9gN3BHsE/QNiBG0EIwTBA6kD6ALNATcBsgAo/wn+0vx7+7/5Wvh09mf1ZPQs85PyyPE48bDw4fDP8DzxVPKS8130QPUY97/4fPl0+8781P1g/zoBbgLTAmkEVwXYBWgG7QZZB60H9ggHCZsI1ggACQQJvgilCBIICwiXCMYHpwYpBvEFRQXWBLYEYwMkA04DxQLbAU8BrgElAf8ATAEUAbwAfQE6Ao4BeQEaAlYCwgIuA8UDagOsA00EHAS6A+sDKgToA8EDiQO3AvsBWgHYAJT/rf6j/XP8Gfux+fj3rPYO9qr09/M683fy3fHZ8bPxifEc8lPz5vOR9Cf2nfdr+Cj61vt3/AX+9v99AdQBfwPdBAMF0QWVBuIGBQdmCAcJQAieCCAJ2giXCL4IcQjCB20Iggg6Bz4GVgb/BeQE5AQ8BDkDXAONA4cCfQGqAfsBRQFTAYsBOgFWAYcCRAKuARcC6AIBA04D7wP9A/YDtgT8BEoESgTZBKUEXwRUBMUD5QKVAiECAgH2/zL/M/7n/MT7Wfp2+DT3APdS9Uv0/vP78lDyNPLg8THxs/H48rXz2PNV9eT2c/f3+Bn7r/vg/Bb/FwGSAdoCmgQHBY8FzQY6BxMH7wdpCfkI0wgxCV8Jmwi+CAcJ7AcBCGoIgweEBtEF2AXPBIIEcASGAw8DQwPvAiEC+wFSAtgB0QETAkEC5gGtAgQDigLMAkcDewOsAyoElwRDBKgE7gSaBE0EswSlBDUEKgTTAxIDSALYASkBAwB4/4r+Sf1C/BX7Vvn19173SvYh9bH04vMi85byr/Ln8dLx8fKZ8+nzyfRN9jH3//cW+v36r/uu/dP/oAC4AZADngQABVYGBQc2B78HbQmXCQAJmgnBCTwJLglDCYYIJAieCB0IvwYwBvsFLQWlBJcEzAMuA2MDSgN5Av4BawIvAiECkQKKAmcC6AKiA1gDIAO+A/IDIwShBPwEtgTnBFoFAAWlBKgErwRYBCcE+QP2AkQC1AEQAREAK/9u/iL9GPzr+j35ofdN90r2FvXG9NvzF/O98qvyJvL88eDy2/Pt87/0TfYD97b33vnh+nv7TP1//4gAQQFAA0YEkwTDBbUG9wZZB+gIaQnICD8JvQkqCegIWwm3CDIIjQhHCCEHFwYpBm8FiQSeBCAETgNOA2oDqQL0AT0CeQI6AlYCzAKKArsCjQNRAxIDeAMABDwEaQTyBO4E4AReBUUFvQS2BPkEswRwBCoEhgOfAgkCcgFoAHj/3v6x/YX8VPvX+RH4Qve99kv11/Q99DfziPJX8vzxafEA8iXzmfOx8y/1cPah9jD4Gvqi+tL7Qf76/30AGgILBFEEAwVoBjMHHgdKCOAJTQk4CfIJywnaCD8JkAl4CG0IogjNB08GzgW5BWIEIARbBHEDuwLsAsUCvAGEATMC4gHKAToCrQIeArQCZgPsAg8DrAMjBAcEkAQtBcgE3QQ4BfwEewSzBO4ERgQZBNoD8wL+AXIB4wC7/wX/bv43/br7rfoT+Ub35/YS9uL0lfS48xDzW/IV8sjxgvFb8k/z3/MM9Lr1jPYV99v4DPr2+l78pv79/48AYAKeA0MECgU6BvQGJQeUCJoJJwk4CcEJdAnWCH4JLgmzCLcIngi/ByIG9AVsBXcEXwQjBG0DxQL6Al0ChwF2AdsB1AGEAToCRALmAa0C1wKVAqkCUQPBA7oDRgSTBGYEWATEBHAE8gNiBF8ECwSzAzkDXQJoAeYAMAAT/0j+nP1C/M/6mPnZ96/2UfYy9bj05vNM87ny8vHk8ZDx1vGy8sPz9PPX9Cf2wfbg9275m/qX+2/9eP9JAGgB/QLyA5oEegWgBvcGcgcZCTUJ9ggxCZAJzAi+CC4JgghOCC4IBAh9BlMFZQWJBAAEAASeA6ICXQKKAq4BAgGAAbgBhwGcAToCoAGnAYoCZwJBAoACVQNOA3gDLgT9A9MDHAR3BKIDlAMSBLcDQAMPA10CMwGBAD4AAf8M/nL9fvwV+6P5Vvis9gT2YPXi9Az0MPPu8vXxyPGl8aHxafJa8wX0YPSU9Wn2VPff+A/6Q/uF/Jz+4f+8AE8CdANRBCYFOgb0BhMHkAg/CRIJCwlKCeQIOQjaCFEI/QfJB7sHrgbuBNkEPASeA54DeAOKAtsBIQKOAacA0QA+AVMBHgGxAW8BDQH3ASgC9wH7AdACIAMWA8UDwQOpA9YDVATPA0MDzwOiA0oD+gJ1AkwBRQAGAPr+zf1Q/WX8C/uR+T74d/al9UT1o/QQ9EXz4PLy8ZDxs/GT8Tjya/NE9F30TvV09jT3ffj++TX7DvwJ/p//WgCAAQsD7wOeBIEFkgaSBpwH5AgACZAIvgjoCN4HMgg8COwHgweDB/sGHAViBEYEvgNjA3QD7ALUAdQBxgHHAHoA7QBdAf8AQQFaAdgAVgHiAekBlQEeAsUCqQIgA1UDQwNHA6IDggO7AuECNQP9ApgCKAI3AQAAkf8B/+n9GP1s/Er7rfkz+JP2nvUF9Y70OvRP86jyDvKX8YnxjPE48jDzL/Ry9GD1afYq97H4E/pD+zj82/2D/2wAtQEZAwQEyASdBWsGkgaVB7cI+QizCKIImwimB9cH7AduB0sHDAeOBtkE9gO6AzIDCAMBA6YCgAFkAVYBiwBCAJIA/wDRAOoAKQG5ACUBygHRAZIB2AGHAocC+gI1A0MDQwOUA4kDnwK3AvoC2gJuAv4BFwHQ/0T/rf5v/av8/PvM+hr5lvcA9h31jvQv9L/z5/JC8tbxX/F08cHxmvKS84r01/Se9db2x/dn+Zj65PvV/Fb+1//DAOIBTgNwBDQFwwV9BtQGnwezCOQInghOCGYIpgeOB3UHNgcTB78GOgaTBHgDZgNAA/YCtwJrAmgBJQEsAX0AKQB6ABQB/wCyANgAiwACAbwB0QGEAacBYAKOAskC7wL6Ai4DWANYA4MCWQKwAsICRAKHAasAhv/Q/k/+Iv0c/DX7JPp2+Jf2WfXN9Cj06fOZ86Hy0vGs8a/xrPF38mTzsfQk9cj10vbL99v40/ru+wP9Gv7T/5YAkgHsAvkDrAReBfgFPgaLBpEHOQgPCOwH2gdnB64GAgfGBo4GiwYwBkIFvgM1Ax0D4QK0AsICNgI6AVYBBgGBAGgA/wA6Ae0A7QD4AKcAKQHUAbEBaAHRAVYCUgKmAt4C3gL9Al8DKwNPAnwC0wK+Ai8CnAGgAHX/8P5L/ib9I/x0+w/6MPhR9g/1tPQQ9N/zcvNz8rPxqPGQ8azxevKg8/f0bvUL9jj3MPhZ+Ur7Yvxa/ZX+YQA6AT0CsAO2BGUF/wV9Br8GAgc1CMUIjQgkCCAIawenBvsGvwZ2BmsGGwYOBVwD4QLhAp8CdQKOAvQB+AA3Af8AUwBQAM4AGwHHAN8A6gCrAEUB2AGqAUwB0QFWAmsCuwIEA/YCLgNfAyQDNgJuArcClQL+AUUBLQDw/mf+h/0t/Dj7QPrY+Pz2PfVu9O3zaPNy8+7y/PGJ8fzx5/Fp8rjz+vT59U32j/fK+Mb5afsw/RP+2/6ZANsBQQKUA+cEhAUbBo4G3wbDBlYHSghKCLsHrQe7B3kGMAZrBuMFzgXRBVMFtwOtAtACnAI2AiwCMwIwAfEAQQGgAPr/lgAQAdgAuQDqALkAxwCuAcoBawGZAWcCdQJyAgQD/QIgA5ADqQPTAlICqQKmAi8CmQHDAIr/pv4J/o/88voI+qr42fYv9Yf0zfMJ80zzq/Ke8UPxvfEH8kLyBfQy9QD21vYm+C/5Nvru+4v9S/58/0gBZwK3AvIDBwVFBfQFeQaqBqoGcgf9B4MHJQf7Bv4GCQbqBRQGYQWLBZIF9QSQA9MC9gKiAmQCOgIeAoABUwGqAbIAPgCkAPEA1QCkAPgAuQDxAG8BQQH0ACkBFwI6AjoCtwK0AswCMgNxA7cCdQLhApUCAgJrAccAZ/95/tv9NPxu+l35/Pe69Uv0BfQ38z/ybPIH8rDwhvCC8fnxMfJP9NP1MfYR9yz5avo/+0X9zf4o/0UArQKUA6ID8gQUBo8F9AW1BoQGTAZdB+gHvwYbBloGGwYqBVcFmQWoBOQERQVmBL4CmAIPA44CLwIhApIBBgF5AcYBmQD6/4gAcwARADsAkgA+ALkAWgG5ABQA0QDGAfABKALMAqYCwgJ4A38DpgKAAuwCigKjAR4BCgCO/rH9x/zC+qf4I/c29eryiPJ38mbx8vAO8STwL+8I8Djx2fGV8/31B/cm90/5cPte/OL9EQB9AOoAGQPPBH4EQgWHBkUGegX7BSwGTAUUBnIHoAbuBAoFGAUHBC4E5wQ8BM8DxAS9BLcC9AELA+UCJQI9AqABgQDtABMC9ACK/9P/GAA9/z3/zP9q/6b/9ADOAHX/yf9TAdsBGgIBAxIDvgKlA34EggOtAjkDMgMJAh4BPgCK/i39c/xj+oz3bvWV81vxkPCe8NTvLO9Z79TuCe617kvwcPGq8xn2gfcs+GD63Pw9/rf/hAECAmcCcAT7Bd8FVgZEB4cGtQWrBYsFrARMBX0GwwUgBPID9gM8A3sDcASsA20DqATuBCADlQJYA0ADrQKmAsMBfQANASwCAgFn/z3/Af9E/kT+o/46/pH+0//X/8b+E/9vAEUB7QH2AgsD2gLPA6wE8gMnAzIDlQJTAV4ARP8Y/S777PmM90H0W/Fd73LuhO467v/t2O2T7a/toO7X71TxivSF94f5rfrg/Hz/GwHFAl8ETQQjBOoFWQf7BlIHwgdIBsgEhQS+A24CpgI/BBkEdQJ5Ap8CygGHAgsEZgO0AmYEpAVKBMgDpQRYBCsDKwNEAiYAQgDpAQ0B5f6V/kT+pPx3/Ez9y/zL/Mb+zP/s/n//UwHpAVYCBASJBBIEJgWZBhsG5wTIBJsDPgG0/47+5Ptr+UH4pfXd8enudOwg6zXr7Or36pvrI+zn7LXut/Ca8vn1LPmQ+zv9DQBcAy0FZAboB7sHqgZuB1gIbgchB5wH/wXWAzkDkQL7AEkAsQH+AZIAMwGKAkQCJwNCBQ4F9gMqBWQGXgUfBT4GzgVDBGoDDAKb/8L+Vf86/lv8CvzS+8/64frS+737CvyL/en+yf+EAd0DEQUXBlkHqgcMB0EHqgcJB/EF3QTJAhQAtf3a+i339/M18cPtJept51vnH+gK6NHoHupI6lzr3+7E8b/04vlk/lcALwKIBX8IswlsCu0KywnTCLYJugmYB6cGAgZHA30AzP8B//f9wv6BAJ0AAwBoAegCQwOXBHYGvwbiBmYIXwnUB+kGXQcwBiQDxwDz/o/8FfxN/IP6//d69yz4nfeT9zr5z/om/Lv+mQErA6AFBAnOCsoKVgtkDFYMEwwsDJYKgActBewCAf/v+s73SPQr8Crtser55sPj8uKj5EHlreWW6GrrP+268Nb1aPih+0EBkwQ7BRMHzgpuDAUM7QsJC7QHDQbYBiYF2wF2ARQBcv7N/W7/QP9P/qsAcQOzA3QEuwcRCo8Kawx/DcMLiwq8C14KTAZ0BHQDBgB+/HX6V/du9O3z2/Mx8pDxh/PF9Xr3OfoM/jQA8wIsB6sK7AyyDysSeBKUEkoS7RA/DsoL6AiMBDAAafyn+Ev0z/DI7JLoZOUH47vgN9+j4NzjkOag6RTupfGY9NH4GP3h/+ED4Qd0CVcK8AupDRYNMwtVCEwFAgJXACYAa/5X/ZL9kv00/bH+bwCZAYYDkgYZCe0KjQ12EAgS8xFSET8PowwcCooHugMh/zj8PfmN9dbxWe9N7XTsHO2y7VnvO/L59vn7fQDLBO8I5QwzEIkTGha3F7YY3RhSFzQUExGeDQ4J5AN8/k/5RPUq8lnvyOxB6iPozObN5VLlxuUZ5iDnf+ux7w7yBPbp+YL78fxZ/6L/MAA9Ak4DvgLtAZwCeAOxARQAfP+4/Y/8CP8NAW8BRgS/B88J0Qs4D2sQWhDsEXoUhRNVEhMSLBGFDj4LVgf0AUL8Jfk29SjwLe0x7B3r3urF66/sOu6a8UT1nPlv/RACkAhODVIRMBX3FjwYvRhiGJgW9ROfEb0OGwsaB54Drf/9+rL3u/T58XTwNvDJ7/rv3fAE8azwS/Di7/TtNO3N78zwdPCP8rv0F/TC9HT27/X59dn3v/g9+U37zP8gA0oEWgaQCGYIhQk8DRIOSg6xEGYSRhPEFJIV7hODEcoPUQ2zCVoGwQThAuj/hP08+0X4QPX38x/yRO9a7tTu8O/E8eX0cPe0+av8pv/3AVEDmQaZCtsMjA5oEBYS5BIAFHcTCRHnDtQMgQodCBAHOAXsAgYB+v4b/WL7R/rN+AD3RPWc9Hnz5/Fj8Pvtg+qi5kHlauZ15W/krOc26o7qQe7c8pH0Ovhe/TAAZwI3Bv4L3A8CEWIUNhZ0E+cTZxZUE2sQExHRD38NJA0gDcoKbQguCJIGHgLa/2UAOf/n/Or8Cvzb+I/3efi29qHyLvG38HnvGvAt8ovzYPVa+Ov75f5oARcGUwuiDT4QHxTGFhwZSxt/HIQamxeHFcES6A3ZCeYGeQHS/KL6a/hq9TP0LPNO8Fbuju5+7R7qzujB58bk0uLl5fLng+Wy6Gntaezf7Y7zavXk9tz8oACcAmEGZAxZEcYR4BM9F6MVABTPF+kWkBO2FIUUIRL3EHkQYg5zChkINwYlAnL+yv0R/fD5i/gK+Jv1ofJw8qTy9O6z7IHtq+377X/wYfNA9ZL4k/zjAFgE+QjgDsIRCRXSGHwcjB2MHpIfPx34GXkWPxMHDjEJAAVQAHD7//el9vf0a/PS8hzygvD98FTxaO5t7HLqFecc4/rg6uMq44PgleQc6MXmceue8T/y1feV/sYBSAZ8DNYThRmOGuMecSG2HbYdgyAsGxoXSxYvEpMP1wwzC6oHBAMiARD+ivmv98T3qPaq9Cj14fXz9Njz8vUh9cHw5e/i77zuF+/d8MfyDvbD+KD9mwNdBpgM3RJCFPYXTR00H7sgFSJ7Iqof+hs1GHsT/gsUBgwCZ/rQ9GzygvHs77/vRPDR7vjtpu9d7pLpSuff5BDgpN5t4rfhgOBS5X3pHulJ7RHyo/RP+bH+7wJuBycOihaRHL0dviGPI8IgtR8lIF0adRYYFGgQIA43CxwKTwfTAln/B/yL+DH24vTR8yPywPJ19LT0CfQd9Z/0NfGn7tXtqOwO7GXtqu9C8iP2G/2aBBwJQRBOF/4aiB6rIz8nHCjVKDQoUySAHy8bxBS5CsUC4PvY8/Lsg+rb6VPptOpJ7Wvuv+8o9PTzovAQ7mTqduTG3/bgTeJD3AvdZORQ483k0uym7zjyyPo+ALUFdA7+Fv0h4iUFKigv4C21KVwrXSUzG3wWOhBUCq4FxgEiAET67/Xl9L3xo++V79Tv0e5k7zPz+fZl99j4l/t2+I70YPST8jruguwx7a7us/ES9ob/4wWxDMIWDxyHIJQmZytOLHgrWSuaKIUjnR7TFzUNlwPE+7XzCepB5MTiSuJX45TmOupi7PXxgPTA8qrvguxc5tDg2uC34N/ayNx2453jbefG7gfyqPb+/XYBrQd3D40X/SEIJjYr1C+wMA0ugS4yJnUcwxVODbEGtQCs+0T6HPZk8+ryofGh8cHwRPAC77juKvJS9Qv28fc5+nX5jvhM+Kz2DvIs7yHwUfEx8Yn2JgAYBWkOKhmIHpUk9ykALagsoCk0KKsjnxy9GMYR1wcUAQf7HvOU68jmx+PE4pnjLuYC6YbrEvFu9CXz+fDf7TXnnOA334Te/tUg2D7fp9/Q5Q7xhvWn/YsGbArkEnAYyB2bJu4nLyr/Li0u6Sq7KiciChmqEakI/wBu+VL0KfNr7yHvTfEl8w/1fvYK+Jr3HPaF97H4BPb+9Gr1G/PE8ZPxgvGZ7mbsAu7I8MDy9/iOAesIQhS8H3oorTCwNUs6mDk7M5Yt4iQpGh4Q5wSf+XjwROre5evh495Z4HrjMua46hfvx/It9475Ovh19Ynw0els44Dg7dqQ0l3Vvte+1gXg7ehr7lD8kQc7D24bSSQmLbs1KzWdOFo4hDOqL80pjRwcEyoKRP8t93LvQOsK6DzmNOjb6sDtefOy92b7o/2R/x4CHgJ//8b9efmO9Dzxne1x63DnbuXq6LPrB/IA+54Dew1LGyQm3i+WN1g7/j6TPPk29C6vI9IYQQzJ/tnxUOim4Pbc3Nnn2FzcLuIz6Y7vPfVE+or+g/9M/TP4hvA1513f+d0G1HvNC9Ko08PUPOLf6GbxaACRDLwVHCLDKZs1RztqO10+pjqANGowviYFFz4LhAHr9qfu6+Yo5Ubi++SY6kXunfLX+S//SgNUBNYEpAWNA+YAG/0H9nfxMO7+6sfo3OMJ5CboSe1L9EL9UwZ7Eocg8ysaNfo6JD+kQWw8QDVgKlAeQBLnBKX2wupR4kXe0Nsp2k/bvuDn56PvIfWR+YD9GwGnAEn8ovUV7Q7j69zq2VfPb8rY0HTSlNYU5Nrr9fZKCIUUOx9vKS0yjzwPPxg97jxLNWUudygPHJUM5gGV+ajxbuqq5YDlkeWt6k3xCPUT+rwB+wa9CTEJBAjiBk8Ctf1m9sDt1ucb5Dzh+N4u3Lzf7+Zr72378QW/EaYhtC9gOrJCiUVMR/ZFFD3vML0iOxR9Btb2q+j23BnX4tWw1hLYutzB5ufxd/tkArwGVwrpC7cINACD9JrnkdtD01jNW79bv3nGI8ma087j0uwNAA4UUiFlLUw4NUHISgxJqUVHP8Y05StpIh4QUv8P9Z7rUuUz3xLdGuCj5AnvnfdF/U8GqA8JFYcV0xKBD+MK/QOl+1nvDOUX4HXbktnz1n/Wet6k6Frzt/+ODE0ZFyoYN5E//UTLRn1H6kHWNqAp6hkaDMb9w+7l4JPYM9b91i3ZAN3N5CTwO/xQBVcKLg3OD70OzQda/dHu3uBc1n3LssQ0u9i7AMTJy5zVkOfz9GoINhzwKX0zoz72RKlK0kZnP3Q2QyyUIdEVsgX89gnv+OjG5G3iNOPm6HTwqfouA1sJrREZGD4aABgPErULUQTQ+aPuGeJY2L3TgNDfz7fR/tUB4eLvSP5dDGoc/iozOZ5FHEvATLNK/UVCPFsttxycDD796e5/4Y3XCNKh05PYl90z5Vzwff26CaoR6RV5Fn0VOhA4BQv2ReQi1HXHyL4ftWeuRbb1v5rJwd1t8J0A9BrELWE5/UQKTFRQ/U9wRu87gS09IAIV+wUa9Jzp+OMF4I7gC+Hv5lnvzPqYB0YPMxYKHl8ijiAwGr8R8weF+7HvzOFm03zMTcmeyHbL+M+12oDqKvuHDBoc6SlTOHRF8krxTNBJgEMyO4suhR4kDd/9qPId5jXcUtZn1mfbAOM26mTzu/5IDAwWXRp5GowYhRSZCp77cup711PGobrFs0mr0acVtZ/BxM6w5ir8yw47KfY6IEXxTJBPulDhSpc7Vy6THnMPvQRd+H3pFeMx48Pkj+jY7VT3+wBkDIIYAB51Ifck9CR3HvIS2gfI+5rs0d+U0r/Gh8HNwajEIcwt1N3iJ/aUCIca7CoDNxtCTUvfTNdJG0JTOMEs9R3SDpj/ZfLp6qfjKd753IbhMOmh8fD5QQLtC9EVNhw8HbIZVBThDacByPFd4DjO+r37sVatyakfplC1mMYY1MDtBQe6GEYyv0MUTAZRwk7SS11D2y8wH5MPjf+U9bbtb+OH4L/lkOxH9bn8KwhfEnUbzSQ7KAQnECUoIVQYDgqo/AvxHOJj1pHMlMO5v8LCEsna0n/cyOtc/8IRDiIPMeE6vUGrR1RGRD8aNUUpHB0fD8MBC/bk7MrpA+h354Tpl/AM+sYB+Qh7DpMT5xhLG4IYRxLWCWACcPcx6P/YYcqHvFS0I6+lr+uvwLp4zePer/EUC/8eIDERQv1JTkoDR05AMjZFJMYQKwMn9n7s8eje5arlze6D+ucErA4RGeUhYigvKy8rciU/Hr8VCQv8/MbueeQl2iXQWsoTx7LF1cl70kfcOOfi9EIFwxWvI7svNDhaPR0/+D2zNicsOiAwFTEJTP1d9CHvcOyj7tbwjvSX+4UEnAvwEPIT0RX9F1YWcRIzCyECtPkA8SLkm9dPy2/APbdQtdu3mrXSvkrSEN/n8UELJRrsK0w9oEPhRUpBbzmNMb8fIA1vABDzVetg6i3oZ+pL9AYBXw58F8kgmigILHotPSsAIjYXSg0LA/P0y+dv38zWXdAtz+HN68320gTcquWn7qP5KQYuE/geSShXLqwxgTNeMncteiQzGpURIwlFAFb5JPXz9Mv3UfvJ/gQEeQs9EbYUaBVfExUTDBHUCzwETftv8wLuh+Qw2r7Rjch6wBW/3MBswPPCatL03/br/wBqEjwdsi61OHg6RThwMr0sSCCeDngDa/im7/DvjfAy8Pv4mQZmEm4c/yNkKtksgixeKZggexNYCJ/+mvIr5nPeTNmd0ynUjdYr1xDal+JV69bx5viDAgILMRMaHI0hcyN1JjsoJCZOIZwazhT1DsUIzANZ/x/9GACfAqID1AaVC3oPfxK3EqgPbQ1BDFwIigJj+kjzye+n6WrhLNqb0hvLQMc9x93Iq8WGzZvcN+Rp8jAGrg+UHOEr7zAnMcMuJCuBJLEW6wkMAgP4ZPS29t703PcnBKEPhRjwHz0mWinUKQ4o9iGLFWIKtQAm99rrNeLg3avZPNeK22Ld3d0p5E3sy/GF9o79mwOoCRcQNhZCGQUbqB64IEYeHhsLGCMU3A8sDH8IhQTkA/sGzQbDBqgJqgyzDsAPMQ4wCyoKUQhwBDP+A/dT8/7voOgH4o7ad9OPzp3KBsviy6LIhNSt4CvmAPdEB5QNBB1iKJgqrSsDKYclYh6jEIYI7QBW+Lz4h/kD+A//3wrkE/cbBCI/J70oaSgTJR0c2xAbBjj88fJN6K3gtt1v2Sza6t7736jigOmx76r0rviA/u8DrQdtDRkTlhSwFwwcZh14HJIa5xjNFaMRQg/7ChsGRQaVB2wFhAX6B7YJ9AqDDDoLMQlbCb8H6APw/Yf4OfX+76jnmOAY2STRfctzyqPLccfsyzfaQeD263z/0AcPEjwiiChdKpkpZyZtIpsXGgz/BRz8evfQ+Vr4M/nWA8gOoxa2HUIkwSctKHAosyIFF10MXQKH+EzuBuQU39ja69fv3NTfvuCw5tjtqvNI+AP9mAL7BesJpA/eEdcR2xYfGbYY1hemFrYUuhKuEGkObQnCB4QKIAlPB/kIAAotCk8MrgvzB7QHLwcxBFz/4vmv9lPznuxc5mvfqdcy0f3M88zby6zIY9K63FjiP/LUAY4H5hWMIvAlFieDJQcjuxy4EE0JYQE6+Yf5u/qn+CH+aQo1E78a5SGKJlEncCgyJpQcGhFkBgD8x/Ii6RbhX93D2ffa8+Co4l3lk+wY8rr2z/oa/nYBIwR8B98KfAwxDk4S/xQaFtsV5hUQFnAUxBOKEdQMWQyeDQ0LngnECRUJIAnPCegHMQVwBCAEgAHc/Jz5MPgl9BfvnOmC4qLcDNakzt7MrM1qyGLOztlp3TXrhP3kA6oQECDHI00nXydJJDcfuhP/CsUDavr0+LT5c/de/MkHhxD1GFwhLybPJ+co1ybLHoUUFgh+/An0deo84m/eFNr72cngiOMd5o3rLvE89pj5x/yt/84AIARfCH4JUwtbD+kRxxRPFtEVtRWTFBcVrxM/DgUNiQ1BCx4LhAr2CCcJ7gkjCsoGwQRFBf0Cef5U+2H4uPQo8B3rw+Tu3aLXwtHNy6XNf8wKymTVad035N32MwIHCa4a1yADJDUn3SJJH3EXQQu6BGz8qPfK+NX31/l3BIwOUhdnIZ8mcym4KpIppSJJGU8M3v7z9FjsFeM13Wja1dju3ePjSues67rxU/gZ+y39GAApANEA4QPZBJMEige5CkoNeRFxEiATmhSOFo0XHhVmEggSMxEbEHcOSAulCW0IxQiIBQUCYALHAGT+evyY+e73nvWC8BnsXOZ23tnYDNHwy7bOj8m5ysLWwtuw5pj5QQHsDOQcvB9LJYol9yA4HXQSigfYAQz6Zfdr+BH42P39CL4SbhxoJEkpHSvGKu4nbx9XFPcGg/pN8c7ojuDP3FPaCdup4fblQenN7tv04vgq+zv97f20/gMAcgEhAiADFwYcCboNnBByEScTpxWQF0oYVhbdE5ATVBP+ESoPkQxXCtMIFgh+BIcB4wCi/yb9B/uK+Sb4MvX98NLsqeaE33PZJNFZzO/NmsnOytjVhtuQ5rH4HgJYDaob3x+jJPAk2x/tGnYQzgVhACX5VPa992f5SQAQCxQVUx8uJ6YrAy1OKycnOB6QEsgEH/iH7pvmi99R3C/bqdwH4zHoyOvh8Bn2p/jp+e/6cfpV+j/7I/yV/UUAtwNKCHAPZhO4FXAYgBvPHO8caxrwFQAUiRK1D0QMGQm1BjcGYQbaA3ICOQMEA7gBpwCK/hv9/vmf9CTwfujR3xTZ0c8vx/bImMd0w1fPQ9jY3470TgMQC40cniJtJygqVyMDHoEUJQaR/+73UPLx8iP25/vHBcgSFB+aKCUvjDIBMNIs9CSsGMQJ4vmA7q3lad0U2XfYJ9i83trmhusO8Q73Evs0/C39Lf0L+3H6P/tR+zT8f/8PAwcKJRCJEloVzhluHCMeyx3PGKoWfBbPE8YQ+gwgCSAILghaBcwCigJPAvABwABS/tj95/ud9+bziO1a5BHekdauy33G3MmFxIDGktRB2mrmr/w3BjYSZyA0I1MpnyZCHwYahwwKABH8ivRi8RP18PmZAXENExy3JvksSDSBM7ku6SleHtQQ5gBl8hfpD+EU2izartl/3BDl8ut/8Mz1sPoc/NL7bfs2+tn2x/cN+En3J/sv/2kEiQ3pEZYU7hk8HbgfwiB0HREZCxjmFXgS3Q4sC7EH7wczBy4EfwOzA74DyAPmAYEAbAAD/JL4UvS76jTjhtxY0h3I48QWyEvCD8gv1i/bAesQAqUJZBZKIoolnSlCJJAdFBXqBdL8MPhx8CHwfPWk/IkEMRNbIhYrYjLVOHk0zi62KCwbowwq++PtF+X93NzYTNrt2V3f2OjC73L0ZPnf/WD+Lfw//ID59/Qq9jL1SPNU96/7ZAEuCTEOahLkFwQdYCGTIm4gQh6THTob/hYRFCcO2ghGCQ0GSAHtAXIBpwDoAjABAgKtAmf/2/1v+HLvRek14SnVecu3wgHCc8SRwfrLVNhj4aT3UAqaD9IeRCZmJ2IoDR/GFrgLRP4z+NLy5u5v83r8dANbDxog9yqFMho6IjnXMMUrISGqEXkCFfI45+LfLNsl2lbbk90h5XPtevJJ91n6Cvzh+kT55/YX9NXykPFb8gL0rvjU/sYGBA4jE/kXOB6MInMkCSU9ITse8hyhGH4U3A+QCdAHnAYrA0sC0AJRA/kEiwVXBUwFUQSHAcj7dvN06w7iNdd/zXjCw7tdwdXASsNm03DdxOw/BLwPvRglJdsl9SgxIjYXVA+cAXD2w/Pt7nzvi/iKAksMzRqqKgozuDlaPkI3EC8gJ6UX6Ah2+ALpMuGm26jY2NoH3fnhE+uy8vX37/pw/Ff9g/rS9kv0ZvDc7RfuLO/58AP3If4lB7YO3RNkG4MhWSUpKWUoyyNYImgfYhksFYIO8wdWBn8DOwD4AE8BLgNPBsYGlQeUCLUGRwNs/EHzi+mu3ljTTsghvS+4sL1HvhbD6tOV4ETwtAcHFHUb9ibdJ2kneR/SFPQKBf4Q9KHx3+6p8KH7vAbpEMYgtC/INsQ8YD+wNqst3CPLE7oEOvTh5R7fDdoq2IPb7t2W41TtS/Ti+Gb7xPxi/Hb4kPWh8VftBOwL7ODs0/Du9v7+vQnmEJcX9R6jJDcptCsNKZkkHSEjHVkXSBFsCpkF4QPtAfsAPQL9A3IHOwqLCnYLCQsBCIMCAfpn7wnks9jkzYPC6LiZtoq9B7+tx4HZYOXW9vYNuBZwHv0msSUbJE0ZEQ/1BCz4nvAM8P/tsvLh/+0LsRZGJ+I0XDqwP+w/8DS/KhQfZg6Y/xTuHOJ/3PnXDdlb3QLgMejB8U/4q/zG/Tr+TfzL9uryW+0R6HTmkOeL6Bns5fRE//wJcBPlG4wiPSohLxMwaivFJjgi3htQFH8NCQaOASIBjf98/0MDHgcCC8EO4w/fDwoP+wp7Axf5xOyf4FfU9sifveS0Z7OkurK/R8gN2tzodfmTD2wZpB4EJxcl9yAaF0wLYQGC9o7ub+4z7tTzmAIYD9gaqirjN/s9PkJjQLs1rik4HaYMafwg7Iffp9ra1ybZ8t294h3rGvUf/HX/aAApAMD8H/d08LjpAuV04vLhZeO65xPwnvufB8MQfRq2IwErGjD8MT4uBilJJEkepxWQDfcGGgKBAFn/IgBOA5wH+gyZEIMRURLCEewMbAUc+7/u/OK+1l3Lq8DJt5C0brcKv43IJNJQ43nz7AKTExcb+RyhIjEeoxZpDocC1vpr82vvbfAy9Sj/hg2oGUAmVzPgPOBBNUAvOtEuBSBtEzIDvfI55nHcV9lr2pfcDuLq6P7vvPjf/Wv+If6Q+1/2xu8N6djjSODC4MHi1+Wq7jL6fQVHEqobgSPsKkEvEjHcLVcokSGqGssT8wwwBpwC+AA6Ac8DsQagChsQ+RI0FHQTXRCRDDEEefmM7czgvNS8yurAR7grtKq3tMKRx0zUz+YO8vID1BUuGIIdtCByGkEW+Qje/xT4E+/D7fDvaPMv//IO8Bv5J/o1vj9JQk1BYzt4K3Me8BD3/iDxoeK/2lbaDNvK343mvezk9Vb+/gH3ATn/k/tx9W3sHuXd3cracdwi3jXiMewp+IsGPxStHFklei35MfIxYS4gJ0QghRlPET8JEgQAADAA3wEnBJcIrA4ZE2oX3RjbFaET8g0OBGv5I+wY3r3Tssm9v1i5ZbWftyjCMszZ03nkEPRzADoRABhNGOIbWxhkEVUITP3r9lvxyu178HT2KQCBD+sdTCnpNCQ/skJOQFo5dCz2HHoPxf9D8e3kkdv72rPdVeFb6JzvqPYQ/ooC/gHf/R75ufJk6aPgDNsa1inVGNmS3jjo8POQA4QVxB7mKfA0pTb6OWw45yw0I/4akRFPBqr96fnU+HD7eQHmBqwNYBdCHu0f0h51HIcVUQnm/VPuz90S0n3Fj7tstu2x0LIevJ3JX9Pm32zya/6DDGkZIxlZF+cYvxFfCAL+yPVx8I/t4u5Z9a79lQt6Hq4pkTRmQOFFAUTRPaQyDCGcEO8CVPLm5GTblNft2kDhRuj28FL5ygDUB7cIawL8/Lr1Z+qO4EbY6NEQ0CXVuNq24lXwsP8cD5gcZyXSLNAwyzKNMJMoax/vF2QRuQqJBLUANwHdBGIJ5A2UEu4YVB6AHyMd+ReAEfkI3Py/757iydYOzoDGysB/vR29LcBVyCbUX9xy5ALzNP3OBVEO1wzcCtQMTwZg/wz5IfTf8xb11fe7/6sK5BcgJ+kvaTfxPUNAPzwHMjImvxaeCJz9SvGk6Dvj5OKW6LjuKPRn+nH/ZwLIA1MAd/cI8HPo+N7I13vSuNA807zZAOJK68D3TAZbE8wcVySWKG4rGC1JKU0jeRvKFQ8SHQ0nCBcGhwd9C8APURPXFlkbJSDgHr8adhWXDfIE1/mM7HjhPNjK0BrMHcdMxcnG2shczVDUxN3a4Rvp+/MM+U/+0wMUAUcDWAQT/yz+1voH/Gv+VwDnBK8OtxdSITYr0zCANLY3qTYCLx4lXBx7DsgDTfyv8rzubeuo7B/yivXD+MH7x/xQ/B36ffP66urjyNyp1gHSm9GI1KfZveJe7Sz41gTKECQcKiJuJUIprygBJmYiWRxPFT0SpxDsDBQL1g1FEIITABj3GlwcSR9iHqEZuhMzDDgEsfmu7j3l2tv71KPQeMxQyUPIOMmkygnQTdjC2w/hoezL8gH6SAHDAEsC3waKArkARP5l/JH/zgBNBOIL+xTSHospQS+PM9025zYkMa8n6x09EdgGg/9K9g7yHu9S7xP1i/ip+u78N/0K/DP5fvI66QDi5dss1szRzdAD1DTZ0uKp6z31+wGsDbAXaB8LIiwlKye4JW4hExytFs8SRBGJDq0Mtw2tEdgVmhm+HEIffCHiIOgcZxaNDecEhft872vl69wv1t7RO8/TzOLL+sxRzgTS/daC3NHetOVI7ojyEPnZ/Lr7pwHRAQX/cf/K/V4AOQP/BSwL7hNAHGsluiz3L50yejNjMDgoyx7KFa8JXAPq/PL2RPX+86/3GPxQ/ar+5v2X++34qPI66WPhg9t81jzTwtGZ1IHZf+Fp7Obz7vwgCe0Q/BgSHRkdox9EIeceJRsrF2kUNBT8E/oRnxGyFLYYxhu6HVAebx+jIFIcVhYfDwYGtP669SDr++OJ3fzY0NYb1BbSMtGc0C/RrNIk153ZCdsC5Gvqb+5X95H5YvsBAykBqwDHAJYAzAN6BQsIiQ4JFrodsCbFK0wu/TBLMKEs9SO0HFQT8giIBcL+8vrU+SH56vzp/qb+qv0A+/X3tfMq7KDjwd3x2KnWx9Q61fHZaN415lnvavXu/IQGfw2TE3gX5xiAG1ofMR7JG14ZKBdwGJQXxxRGFNAWGxroHPkdkB15H5wfEBsNFUANSQXp/ff0pess5UjgXNwJ2z/YoNW11LPS6NG40GrSQNbm1DzddObK6DfzE/rk+18EDgSzAzwD+gJKBK8ETAYzC6gTqxlCI5wq/y3vMC4x+y7CJoAfyBc+C6YHiwEf/WL8sPr0/ab/av+u/TX7HPcx8pvrI+NU3SbZINeG1pTWrdv+36rlaO5k85L4tQDUB7sM4hBaFTUYSh1yHwoeRh3QG44bGBo5F7wVXRYqGEga/RwjHcQeOiCDHOQXAhHoCLwA/Pdy76/nyOIU3/ncOttK2LfWMNUB0lPQBdHL01jSUdhV4Tblcu/x93n52AF7BDkDZAIJAeYB3wF/AwsIpA/iFbEgVioYLo0xOzJjMGAqxSE+Gg8NYwiaBJ//rf6O/YsAkAM5A1oBsf3p+Hz0x+3H43fdfdmG13TXBNcz22TfN+RU7M/wiPLY+Nf+bwWaCb8MIRI0GaseHSFXH6EenyCSH/QachYoFpsX7hgXG9Abvhy/IOIfRBv0FDwOzQag/eL0zu145kzjoeLt3zzdIdsu2CXV0NHLzvjOxM770HPZ/96i5tLyVvi1/SAD7wIoAu//L/7b/cb93ABOCDMQHBmjJcstZjE+NHozMy9LJq8eVBOFCcMG5QJvARABmAL+Bt4HXQcZBHn9G/jO8iLptODa223YZdl92c3a9N7L4q7o3+3f7lTxmvaT+98BsgWJCJkQDhmmHPweXx0gHWgfnxyiF8QU8BWoGDYbOB3HHpghfiNjIa0bqBOqDCAEbfuc837tOOiv5wfoWeXy4orgwdxb2C7Te832zGXO2c6g1azdgOQm8pr3HPvVAHX/iv6T/PT4/vi0+mr/hwY6EFsZfyZBLwQxcDI9MMkrzyLiGm8Q7wh/CCEHKwguCDQKxA7IDuUM+AV9/Xr3bfEx6GfgeNwC24jeDd8l4FDjbea46iPtzOu66yHvkfSb+kwAMQT/CuUWtxzoHOQcOhv3G3wbqhVrEW0SxBiwHBUepx+rI1YliCNfHeQT9AtTBU/+r/Zf8N/uee6E7prtZOn05Ljf+Nk806XNrstvy1jOz9fA3rfm7vGo95f7a/3b+az2qvMS8ZvwsfOU+v0Dcw89G4UnuS4uMQEx5CzJJpodGxWbDXcJxAmOC4wO7RAjFF0WyhUzERUJ0P+L+InxrulQ49Pgf+F25KblEuaz5zPpg+ov6tnnqeaq6cru2PPb+Tb/awe/EZEWghdZF4oWlxdZFvkSqhExE/UYyB0CILchLSQKJC4ihxsqE3wMJQfbARv9Gvk++Kf4yvg49mLxWOs+5Avcr9OwzRvLUszAzujXIeDg54XyKve4+E/55fQ98HjrkuhW6aTthvUNANQLRxfmJOErES0kLNomhiHSGTkS2wwVCqYM/hDAFOkWJRrlGzMa5hTwC60CofuQ9kfwwuoU6Rfq/OzR7QfsCOs26sPpHunl5cfjs+Zt7JrxvvX0+LkAbQhsCv4M+wuSCowPVhANEA4TLxZyG0EgRiNwI6khsSBwHm0YEBE2DG0JZweHBvUExQMcBI8FfQFU+8X12eyO5HjckNJxzY/O/dHY1DbbPuTw6g7yUvVM86XxKO/66hnmhOTV6ADtFfZQACAJ3RLdHIUj4CNjIb0d3xooF88SOhBlDz8TsBccGX4Zzhl2Gv0XhhL7CugDHwD7/Yr6Nfa/8xP0QPVy82vutOq86bnoH+ip5tvltemJ8FL1dPYD+Ef6pv4FAnX/uP7pAaAGuAwlECMTQhmcH3QiOSERH5QcjBmYFs8SIw4GC8IMrA4xDj8ORw0zDD8KDAem/0L3pfFR64vjJ9wg10DWYdod3Cnec+NG5w7tHPGv7T/tB+1B6ojoseXT5kPrEvFW+Jv/mQUuDUEWAxo+GqgZTRgLGOIVVBO4EUERBhXpFtsVZBVAFycYbxW3Er4NFQmVB8MFOwD5+475mvfy9gLzVu8e7qTtuO5576/tZO5p8nj16/Wc9CXzHvR+9i/5mve/+NEAbgdWDBcRCRU4GUMdaR1JGf8UmhTzEXcPGQ7UDBkNCRAHE2MSRBFoEOcO5gqPBXz/1Phv8xfvYug14lreWt8Y41zh6eRo6enpqu8Y8hjtV+2Q7IfpPObx43LlQuiA7qr0EfxWAYIJjRIQFTYWDRX8E9oSHA9/DW8L/gseEM8SuhOaFAcZhBppGNAWexIsDHAKuwdPAW7+uvup+hX7TPjy9ib34Pb49wP44vQa9C72s/Yr9ery5PDB8EbyefSU9SD2fP61Bn4JVA7kEs4URBdxF/4Rhg1SDCkLkwkOCtwKyA0vEYUUVhYqFNMS7RATDIEFpv9E+tv0W/Li7kjqW+cA5/PqPOwF6n3uh+4o7+Dyp+7U6qXrrukH58bka+TE5/XsVvMT+Wf/0AJWC08Q4w/PDqMM8AtmCY4HOgdaBqsKMBBfE4EUwhaqGncZzBeaFLMNMgjvB/IDfP+x/tv9BgAGAYb/CgBE/wj/ov9Q/Jb3d/ae9n/1BfTu8ejwZfLv9Qn5g/l+/KgELgkxCjUNgg1xDcgO7Ay7B0IFVgYoB/0ICQvMDVoQRhOnFSMU8Q+GDREK0gRq/y77UPdq9Uv1dvN08BvuDvEo9CjwMfJQ8s3vj/Jw8QTsjurz6n3pdOeQ59TpZe3U8/T4cv5hADsF5wlDCfYH1QU8BHsD8wJqA34EBAjyDeQSDRViFI0XZBYHE/QQRQuWBQMFBwTUAW4CJAPOBc0HlQYpBmYExgFTAcn+5fll99n31feo91f3/PZM+Gf6nfzR/X398AHtBjcGMwfhCFkHvwfBCEwFJwMSBK4FnwfnCSwM+Q5WEBoRxhBSDH8IVgZSAtH9Kvsv+dL3a/gT+Z72F/RZ9ZX4vfJE9GT0gvDk8bnyKe7k7DvtVO2N6zzs4u5179707fj4/MP9XQG9BCoEOQOnAQ0BMwGSACsDUQSgBkQM3A+iEhMRPBNSEdYNlQzBCOgDqASXBNYDZQWABswIvArvCDUIxwVBAvsAFv8A/Hz5bvrE+yP8O/z4/O39L/4NAG8AVv6ZAcgEcQOlBHkGBwV6BaoG3QSeAz8EQgX3Bs8IoQn0C3wMcgy/C5cIBwXMAs4Ajv3I+7r7ePp1+qn6JfmQ9an1nPhQ8hf0tPQV8TrzpvRi8Q7xxfCQ8FPuCe+C8EfwefSa9zz7OPxV/2cCQQIoAsMA/f+8AGr/SwK3AzsF+QnsDB8PGQ5kELMNgQqkCkEHngPnBPkE8gTiBhYIJwnHCqUI3gccBfQB3wDz/sP9cPxh/QH/wv8pAAYBVgGG/5kBdgBL/loBigKVARkEUAV+BJkFkgY4BYIEMQVRBN8FOgeRBwcJQwkACWoIlQYuBHYBQgBk/gD8jPyv+3H6YPqO+aL1WfVy+M7yrfRf9pPyWfST9kHzN/N68j/xpu9W7zzxyPDD87L39/nd+/P++ADHACwBzP+4/ln/jv40AA8DlwPGB+0K8wwsDOsNEAxRCHAJYQZRA9kEvQTSBFIHAQjBCOcJZgg2B0IFDALRAfr/tP/s/h3/PgHiAVkCGQNnAo4BQQIsAcz/owH7Ac0BHASaBCoEKgX0BRkE0gSsBE4DrARIBosFrgZLBxcGjwXkBEQC0P8W/zT97vus+/L6g/m7+e730/Xy9h/3yvP895D1cvSo9uj1ffMM9F7yRvFP73DxMfKz8c/2F/lj+tz8jf/X/nz/Fv/3/bL8T/5T/Q0BFwKFBCsIGAr7CkELfQsSCBMHFwd0A4IDtgQjBCUGOgeXCHQIHAmcB4AGggNuAoQBMADxAGgATwEgA0cDrwSeBI0DJAMWAywBzgACAq4A+wH2A3gD3QOnBSMFjARvBW0EdANbBK8E2gNiBEYEUQPvAp8CiADi/j3+4/yv+yf7v/mH+Lb32vUS9i33u/Qz+Pj3TfZC92z3tPRS9EHz1vFW76nwevK68XX1IfkB+n77YP4l/i39G/3u/Nb6Cvxz/GD+tQCfAmQG9gcHCYUJhQkzB1cFkgVHA5ECKgRDBLkFWgZ/CEAItAfzB28G0wPaApgCGwFaASUCVgIyA/0D6wQjBMwDiQOpAhACpwFuAukBjgIHBOQD6APSBG0E/QPrA54DMgN4AwQEDgQnBOgDfwNrAsYBYQDU/rz90vwV/Fv7wvoM+vf4y/cZ9k32HPbl9Jr3y/Y49r33DvdO9ez08PP88VXw3fFm8VfywfUG+Ir5jPuL/W/91fzg/K/7RPpU+3T7xv1j/xcC7gSOBskHFgi7B9gFWAQVBL8BwwEEA5sDFQVTBv0HjgexB24HrgWGA7sCUgIpAWsBhwLJAugDOwWnBaUEiQQcBMkCNgIQAjoC5gFxA0ME4QOoBBEFkwQEBOQD7wKmAiADSgN0A6UDhgNmA1kCaAHo/z3+Iv0f/Hv7ovrw+Rb6JfkU+Lb27vZm9nH1x/dw9uH1mvfI9nX1UvVy9PTytvGv8iryj/JZ9Wn3rvg2+jT85Pst/Bj8WPtH+tP6Rvv1/Gv+bwDvAq8EjwVMBu0FcASsA0oDsQFaAYMCCAOTBI8F2wbfBtgGLAerBQ4EagPCAj0CgAIdA4kDyAS5BT4GpwU4Ba8EqQMSA4ACWQK0Ao0DVAR0BO4E+QTrBLoExQP2AoMCigJ1AuECzAKmAtcCHgJFAb7/h/5T/SP8fvtc+vP5lflW+Zz4Yvcq92n3dPbq91735PZ+9xz3LvZ49Yf00fPE8uryFPN58xb1JveL+ID55Poc+zj79vqY+un58/m3+gD8ZP3l/hAB0AKQAzEEMQQnA60CYAJdAQ0B7QFrAs8DyASSBToGVgZ5BqcFrATTA3EDOQNjA3sDIwQ4BY8FSAZIBqAFTAXnBDEEeANqA74D4QOvBOAE+QT5BAoFkwS3AxYDtwKHAmsCsAKfAooCigIaAosBBgAy/0j+0vxe/JP7MfvW+r76YPo6+ZL4w/jn99X3Yfgi+Of3gPj19yP3afby9Rb1EPRB9F30efT99Un3Rfg2+VL6vvqp+pj6UvrJ+ff5Wfpi+1D8zf1u/6AANwHmAfcBsQFvATMB6gC8ADMB+wHCAh0DXwTLBLoEOAXEBBUEBATFA9MDtwMnBNIEGAWdBQIG1QXHBZIFIwXPBGIEcASsBMEEBwUOBRwFxASeBDgEQwMLA9oCkQKtAhkDGQP6AiQDtALYAfgAOwAB/yz+qv0Y/b384/yv/FT80vs8+076Afpn+RP5UvlP+Wf5sfmV+f74nPjg9932IPbP9ZD1rPV09h/3zvfU+Jz5Afpc+lL6K/rQ+eL58Plc+iD7B/wK/RP+v/5u/9r/+v/2//r/yf/J/x8AQgDVAGEB5gGHAvoCRwONA20DwQNxA40DzAObAwcEXwSeBPwENAV9BYEFaAVlBUIFLQUYBRUF6wShBIUESgQZBMgDwQO3A6ID/QMqBAQEKgQqBNoDPAPoAjYCXQEGAWUAEQDM/7f/zP+D/0T/8P5L/pX98fwY/F/7TfvW+lT7hfuv+/n7vftm+436v/mu+Ij3A/dm9j/2k/Yt9873lfh1+cL5Nvpj+hP64vmY+Yf5bvnN+T36xfqh+1786vyL/e39F/4e/jb+LP4z/pz+yf4v/77/DQCgADcBeQHRAQICOgJLAm4CcgKDArcCCwNjA7ADKgSMBKwEAAX5BN0E2QSsBIkEPAQgBC4EFQQ/BH4EvQQABVAFjwWIBXMFUwX5BK8EWAQABKwDagM5AyAD7wLeAskCjgJZAv4BlQElAZIAGwB///D+gP4C/pX9N/31/Kv8bPwq/Nb7dPsL+3/65flB+a74OvjS96T3jPeP97n3//dI+JX41Pgv+VL5ivmV+bT51Pnl+Rb6S/qK+uH6Nfuh+w78j/zu/F79xv0e/pH+1P4v/2f/kf/X//3/LQBeAJIA3wAwAYQB7QFBApEC/QJAA3gDqQPaA+gDCwQqBDgESgRYBHsEhQSeBLYE2QQDBRgFOwVQBWEFegWEBY8FiAWBBXMFPgUfBfIEugR+BE0ECwTFA6IDagMgA9oCmAJWAgkCpwE3AbUAMACf/wH/ZP7U/T793Pxw/C387vus+377Q/v5+pv6RPrX+Vn57fiS+EH4H/gU+Dr4Xfij+AX5ZPmj+en5JPpA+lz6g/qY+rv6APsx+3v7y/sx/IX87vxQ/aD97f1L/pz+8/45/4r/zP8YAFAAiwC8AOoACQEzAVMBhAGxAfcBSAKRAuECNQN4A8ED9gMcBD8ERgRKBEMESgRiBHAEkASoBMsE+QQVBTQFQgVMBVMFQgUqBREF7gTIBKUEZgRDBAQE6AOpA3sDSgMWA+gCqQJgAhoC0QGEASkBzgBvAPr/lP8o/7/+T/7p/Zn9Sf38/L38hfxX/C38+fvI+577bfs8+/n6zPqf+nz6Z/pV+lL6Z/qG+qL6xfrk+gv7I/tD+1/7gvuo++T7Jvxi/KH84Pwb/Vr9oP3f/R7+T/6V/tD+DP9H/43/0/8NAFoAmQDYAA0BMAFdAYcBvAHtAR4CUgJ5Aq0C1wIBAy4DSgNjA3sDjQOsA8ED0wPoA/0DEgQjBDUEPAQ4BDgEOAQuBBwEBwQHBOQD1gPPA7ADngOGA2MDQwMdAwgD2gK+AoMCbgI9AhMC5gGnAXYBRQH7AMoAkgBJABgA1/+f/2f/Nv8F/9T+lf5d/ij+Bf68/ZL9gP0m/Qr9GP2y/Kv8y/xp/Hr8hfxN/HP8XvxJ/Ff8O/xG/F78Tfxw/IX8mvyr/Nz8FP0t/V79p/3G/f79L/5d/q3+xv4I/0v/Z/+w/9f/AwBCAGEAnQC5AN8ACQElAVMBeQGOAbEBzQHwAQkCHgI9Ak8CWQJuAnwCkQKRApUCnwKmAqkCqQK3ArsCuwLCAsICwgK7ArcCsAKfAooClQJ8AmQCawJSAj0CLwIhAhoCEAL3Ad8B3wHNAbgBpwGLAXkBZAFTAUUBMwEbAQIB7QDcALwAqwCBAGwAUAA0ABQAAADe/8X/rf+R/3X/Uv82/xb/Bf/e/r/+pv6D/nX+Vv49/iz+F/4J/gL+7f3f/dT90f3Y/dT9zf3K/dH92P3t/QL+Bf4e/jr+SP5u/of+nP6//tT+5f4M/yH/Nv9L/2D/fP+K/5H/ov/C/9D/5f8AAAAABgAbAC0ANwBFAFoAbAB6AIgAmQCgALIAwwDVAOMA7QDxAAkBDQEbASIBLAE6AT4BTAFFAVYBYQFvAWsBdgGEAZIBkgGjAa4BuAG8AdQB0QHiAeYB8AECAv4BDAIJAhMCEAIQAhoCHgIhAhMCEAIFAvAB5gHYAcYBrgGZAX0BawFPAToBEAH7ANUAqwCSAGgAQgANAPb/0P+b/2f/Of8T/+L+sf6A/lL+KP7w/dH9qv2A/WT9Rf0w/Rj9A/31/Nz85/zV/Mv8y/zH/NX83Pzc/Or8/PwD/SL9N/1M/V79b/2H/Zn9uP3N/e39Av4h/i/+S/5k/nz+nP6x/tT+7P4F/yv/Of9Z/3X/g/+p/8X/6P/6/xQALQBJAGEAegCSALIAwwDqAA0BFwEzAUgBXQF9AZIBuAHDAdgB6QH7ARMCLAIvAksCSAJWAmQCbgJyAnwCgwKAAocCigJ5Am4CfAJZAlICRAIhAhoCBQLbAdEBsQGOAXYBSAEeAQYB1QCyAHoASQAUAOX/t/+D/0f/E//U/pz+cv4o/vv9w/2S/WT9Lf3//NL8pPyF/E38OPwV/Pz77vvW+7b7s/uo+577nvus+6/7uvvI+9b75/sD/Bj8OPxJ/HD8k/y2/Mf85/z8/Bv9Rf1k/YT9o/28/eb9Av4e/j3+YP6H/qb+zf7p/gX/KP9O/3H/kf+t/8z/7//9/x8ANwBaAHoAjwCnAMMA3wDtAAkBFwE3AUUBWgFoAXkBhwGcAZkBoAGqAbUBsQG/AcoBxgG8AcYBwwHGAbUBsQGgAYQBiwF9AWsBaAFPAToBJQEUAQYB2ADAAK4AiABlAEUAMAAAAOj/xf+m/3//Uv8v/wX/1/6q/p/+RP5P/v79mf2//XL9FP1J/dn8r/y5/GL8QvxQ/Pn78vvk+7P7nvue+4n7gvuC+3D7X/t3+2L7X/tw+2n7fvuQ+5D7rPu9+8/7A/wY/DH8W/xw/IH8qPzO/Or8FP0t/VD9dv2H/bj94v3m/RD+Ov5I/nL+h/6f/rT+4v7s/ij/Of9c/3//lP+p/9D/6P8GABsAOwBMAHMAcwCLALUAsgDDANUA3ADxAO0A+AANAQYBDQEbARcBGwEiASIBFAEXASUB/wACAfgA3ADmAMcAzgDAALIAiwCWAG8AZQBTAEIAGAANAO//xf++/5T/df9j/0D/L/8I/+X+0P67/pX+bv5S/h7+EP7U/bH9kv1o/WT9N/0R/Qb9y/yy/Iz8afxQ/EL8I/wj/AP85/vn+9L7yPu2+6z7pfue+5P7kPuQ+5D7mvu9+6j7xPvk++77A/wH/Bj8OPw//HD8hfyF/L38y/zj/BT9N/1F/Wj9gP2n/dH95v0a/kH+h/6t/t7+Of82/4b/f/+K/63/hv/v/5H/rf/6//P/AwAbADsAMAA+AG8AMACWAKAAdgCLANwAUAC8ADoBkgDmAPEARQAGAfgAfQDAAKQAiwDAAJYAGwHOAMAAvABJAJkAOwCWAOoApABoAM4AQP92AHH/qf+m/1z/Z/9n/x3/JP/3/uz+h/73/r/+RP5y/lb+S/77/f79rv3m/cr9p/3D/VP9kv0R/cv8V/25/B/9Iv2M/LL8V/z1+4z8d/z5+4z8W/wt/Jb8cPwt/BX8afz5+yb8r/z1+1f8svwD/Kv8mvxw/EL9d/zS/AP9A/0Y/UX9UP3D/bH9v/30/UH+5v0s/o7+bv6V/nz+If/N/kD/eP+H/m7/av8DALf/5f/2/5H/egA7ADAAlgAiAFoA1QDOACkAMAHjAJH/9wE3ACIAoAGR/9gApwB6AI8AygCt/1cA/wAUAOX/6gCt/yYAVwCY/4sAeP/v//r/yf8a/+H/tP/i/iYApv+Y/hQA5f60/mr/D/8T/yj/Wf4o/4r+df7w/p/+SP7X/i/+fP5d/jb+Xf7z/rH9bv6q/c39LP4+/ff9kv3N/Wj90f3f/ZX9TP28/V79Gv5a/aD9hP3b/WH9ef1e/TT9yv1F/dj9Sf12/Rj9V/2g/Wj9Df3N/S39KP7D/XL9/v2//UX9Z/5r/RP+cv7p/V79Cf6u/Qz+2/7m/YD+RP4h/pH+rf5S/mf+JP9n/yH/Z/82/9f/9/5j/1L/bv/T/14Af/9MALv/5f/z/2UANwCEAAAAaABQAFMAiABoANwApwBMAMAAMABoALwAqwC5AN7/oABMAKsAzgDX/zcAegCG/4gAUAAfAJIAvv8tABQAav9lAKL/bv+gALH+NwCK/4b/sf5q/3//R/8M/w//8/60/jn/sf4r/8L+Uv6H/o7+Nv6R/lb+zf2//rz9lf3G/pn9L/46/rj+a/2c/bH9EP4N/Wf+zvyE/WD+fvwh/hP+Cv2f/lf9Qf4M/jD9Jv12/dH9Uv7K/QX+xv1o/UT+SP4o/q79CP9y/Rf+LP5E/sr9Vf+H/nX+K/89/+b9Nv9W/pH/sf6Y/zb/tP8W/9P/rf6m/9f/wv+G//3/Pf/v/zsA6f43AND/PgD6/3YAbwCR/64ATv/jALf/TAHv//sAKQBn/9gAhAD2/30AGwCIAIEA6P/OAEUAFABeAP3/qwCt/3YA1//2/yYAdgAr/xEAPgAB/4r/tQC//sL/LQDl/goACP+R/5H/h/5//zb+D//e/2T+bv/l/iv/lf6b/1b+ZP7U/pz+0P5W/ob/gP0J/hP+nP4l/qr+xv27/iX+oP2m/lr9gP5a/Xz+zf0v/mv95v1u/rj9u/6K/h/9Nv49/lP9sf7G/kv+5f5c//f9RP89/sn+tP4o//b/Qf4W/4f+0P/+/oP/BgDw/i//JP9V/3YARP8y/wYAEQBu/xQAOf/Q/9EA9/4NAJYAf//s/1L/UwCN/zAA+v/M/14Ag/9TAFn/KQD6//P/PgDs/yH/fQAT/14ARQA7AAYA1QBc/xgAlP8NAOH/9v8GALD/7/8F/0D/u/+V/vb/XP9u/2P/jf8d/1n/Bf+q/qP+bv8v/gH/g/54/7/9+v6//gz+0/9T/fP+6f1c/2T+rf9y/oD+E/8F/nH/bv6Y/gn+Of/X/nL+3v/7/Uv/JP/G/g//sP+4/vr+RP/s/ln+JP8k/wX/xf85/+X+cf/l/pz+CP+x/hP/Hf9d/kD/If9E/7j+5f9//3X/1/73/hgAGv5oAEH+GwBq/yH/Hf8o/z3/n/85/+H/Y/8y/5//t/9j/y//qf/6/0v/wwBn/jAAlP8a/98ACP9u//b/QP+D/yIAHwDG/kUA3v+0/xP/JQH+/ZYAWf4F/3H/mP79/6b/CP82/2D/Fv89/yH/cf8F/xP/n//w/sn+2v95/kf/rf6U//D9fP/U/nj/3v7+/or+Cf7N/sn+zf4T/w//Uv8o/n//SP6Y/h7+Nv/N/YP+rf4C/p/+QP8e/h3/mP7J/qr+Wf55/vP+Gv+x/jr+8P5L/uL+o/4B/1z/3/1A/5j+jf/G/v3/Ov5hAKL/8P3KAOX+qv7M/zb/g/60/pv/3/3T/6b+BgDG/mgA/v4RAIb/E/8k/wAAxv47AAj/+v54/wj/CP9u/2f/bv80AAX/SQDJ/pH/E//6/+H/3v5TABP/8P6t/yv/4f9c/zb//v5c/9D+2v9L/3z//v5g/77/av9u//P+Pf8T/83+lP89/9H9hv/l/v7+Vf+D/jb/jv6i/zb+RP/b/lb+KP/s/vf+6f4X/ln/v/1V/5L9jv4o/3L+Xf6R/nX+kf4Q/pH+yf4J/l3+gP70/UT+5f6g/aL/CP+R/uz/Ov6w/xj91/+L/en+bv6m/pH+tP7J/q3+Of9r/tr/1P0r/wL+1/+x/fr/bv4T/4D+pv/U/QYAjv39/yX+XP+L/Yr/n/5P/h8Av/54/27/Mv9S/rD/iv4P/zL/sP+Y/goAwv5hAJz+0/9q/wX/iwAv/2EAS/+b/3//Y//0AE/+MACK/hr/zP+m/gj/QP9O/63+XgDe/mP/S/9V/0H+3v8W/wj/6f6IAAL+5f8Q/pH/uP76/i//qv4k/0j+E/9B/nX//v1P/nL+lf5Z/6D9zP/3/Tb+CP+c/fr+Av7s/kv+Pf6O/kT+Ov5y/r/+S/7O/Kb+Nv7m/ab+mP7w/R3/Pf6f/jP+av9X/Tb/i/0a/0T+g/6O/oD+S/63/+L9S/+D/tv9Wf+H/oD+hv/i/f7+S/6j/nL+Bf6K/yj+vP0wAGH9RP8d/1L+bv91/lX/5f7l/u//EP60/5/+1/6f//P+ZP6b/3L+vv/i/uz+sf6//kv/Tv/l/lX/3v6i/wH/sP+b/8z/xv5H/5X+L//z/kD/Y/8h/9D+cf/w/pH+wv8C/vr/qv18/1D9AAAo/nH/h/45/8n+yf5A/y/+Pf+c/s3+E//G/un+9/2N/839df8T/uX+o/1j/0v+7P7w/dj9qv5e/a3+Bv0o/wL+oP0k/7j+qv0r/9j9YP5S/k7/7vztAGv9+v5y/WD/aP0a/+39tP7D/Y7+F/5W/m7+3v68/cz/S/7D/UH+3v5u/qb+v/7Q/ij+kf4l/j3+If4v/wz+Nv8s/jb+rf64/kT+8/7p/V3+ZP7l/nL+Tv+j/o3/E/5n/yv/3/3N/v3/F/76/rT/h/6m/ob/ef7Q/kv/CP9n/j3+kf98/ob/v/45/zb+xv4h/y/+JP/3/pX+kf9g/4f+bv+H/i//Wf8F/7T+CP8r/9D+8/42/9T9u//3/UT/Qf58/2j9Uv+8/ZX+Mv+f/mD/yv1g/wH/5v05/xP+o/6D/vD9g/+V/cL+7f0h/oD+Gv6b//T9h/64/rT+fP4Q/pH/2/0z/jL/fP73/ub9E/8l/ln+Mv+V/cn+sf7i/nb9hv8Q/j3//v0W/5n9o/7N/tD+1P6q/T3+h/7U/VL+0P6A/en+uP15/hr/Uv5u/2f+RP7G/nX+df6t/tv+ZP7N/jb/3v7b/vD+o/6t/mD+Of8C/s3+Z/7U/uz+bv5g/vf+sf6m/uX/5f7w/uX+L/95/g//Af9d/qb+4f8T/ob/7P6K/wz+0/+t/kj+WgAT/tf/If7o/z79t//N/cX/M/40AEL9yf/Y/QoAh/4h/8L+eP+q/s3+yf5L/mf/N/2i/w39JP9y/tD+Wf6R/uX+tf3J/yb93v+Z/UIAef1CAP79Af9k/ij/cf89/vf+mP7J/sL+df4T/3b9tP+//vP+YP4I/+L+If55/rT/+Py//mf/i/2x/k7/Av4mAJL9Nv8v/j3/L/7o/5X9fP7Q/jr+Af+4/mwAJv36/rv+gP6//tf+pv+H/e//7f3l/4T9FAF9/dP/E/5S/7v++v+x/ln/pv6+/6r+zf5g/xr+0/8a/i//iv4a/2f+rf/+/gz/If9W/v7+Vf8r/5j+D/95/iH/Y//3/nj/tP7X/ij/eP9u/vr/Bf/z/rv+mP+c/jL/XP9S/jr+6P+g/QAAdf4W/zr+4f/8/GEASP4W/+z+BgAo/hb/wv86/kT/L//J/m7/sf5A/yH/RP9r/oP/DP9Z/5j/9/4F/k7/L/5FAID+AAAl/uz+h/6D/0v/KP7w/qn/Xf4iAK3+hv+A/vr/Hv4r//7+uP7Q/+L9/f9S/rf/hP0DAN7+4v7s/xb/wv6kAID9GAAB/0H+GABu/nH/nP5n/xr/E/7OAMr9lgBZ/nX/8/9n/k/+CQH0/Wf/YP7z/rv/sf4B/1X/lf4UAGf+EQAW/8b+5f/6/gAAlP89/xP/u/8r/47+t/89/27/BgBP/pH/rf6t/i//5f54/zP+qf85/yj/EQCj/QAAK/9I/gMARP6Y/4P/g/8a/8n/F/56APr+av+t/sn/xv7b/j3/fP5n/3j/SQCR/z3/iv+K/zn/Wf8YADn/E//M/2r/Y//U/rv/AwAr//D++v/6/0T/mP/i/lz/fP6t/+L+If/F/zL/2/4AALH+iv9u/0f/RQDJ/uz/u/61AM3+EQDp/nMAyf7e/yv/Tv/s/gj/2v9q//P+MABE/0v/CgBL/2EAZ/+0/8z/kf8F/0IAsP/+/qL/QP9x/+X+pACt/uj/4f+Y/3z/6f6Y/1n/iv+3/3X/nP4iAEf/Fv9QAM3+lP8DAFX/SQDJ//f+/f/T/3L+AgH+/o3/XP+3/2f/2/7KAJX9bwD7/Wr/FAD3/t7/Bf5eAPD+4f+IAEH+8/8AAEUAsP+IAB3/PgDU/jAAbAA2/x8AGv+IAAH/AABS/vQAnP6ZAAAAXP82/8z/RQCx/kkAOwDp/mEBM/7l/zb/df+Y/3YA2/56AGD/R/8v/yYABgAo/9wA8/6m/zAAK/+IABsA2/49/5j//f/Q/woA5f9TAMz/DQBQAOH/Tv/0AGr/If/DAL7/Hf8iAAYAIf9JALv/f/9O/w0AE/8wAIb/u/8iAGP/wwBx/5YAmP+N/5H/qf+t/+H/wv+3/1z/xf9aAKn/YQAv/3j/Z//X/woAm/+U/9v+qf8UADn/K/9XAL/+qwDw/qQAAf8NAP3/7P8r/30Af/9JAHH/lgBd/jMBmP5MAB3/iv8d/9r/kf+t/kUAjf+D/8z/3wAr/+j/ZQAwAKb/fP8bAWD/YQDN/hQBgP4+AND/bACU/+//m/+i/63/n/80AID+0/9j/+z/pv89/8oAm/8YAND/7/9S/1n/TAD6/2f/zP+kAPP/Tv8YAOz/Z/+3//QA3v5zAAX/HgGm/yYACgDjALT+2ABn/+H/XgDQ/3MA1/9eAHH/RQDv/1L/pwCG/xQAt/9j/8n/6f4wAFMAIf8pAGP/Fv8RAA0AYP8wAFX/SQCK/xQAt/+m/1AATv/6//b/xv6LAMn+TACj/hcBmP7jAI3/u/8fABb/0P9g/4gAcf+LACT/R/9TAIP/sP8k/yIAOf87AHH/LQAM/6QARP8pAFMALQCb//r/6P/+/kgBdf43AIr/1/9H/yH/7QB1/5j/MAA3ANT+UADl/97/E/9zAD3/EQB//9D/u/9S/14AR/8AACT/DQCi/xgAcf87ACv/NACf/0wAjf9QAMAAfP4XAdUABf83AJ//QgBx/0wAov80ALv/NwA5/+//uQCY/14ANv9sAJH/Hf8mAKn/S//o/4EATv/a/3j/u//Q/4b/NwCb//3/7//a/8z/jf/e/8z/S/9FAOn+JgB1/z4AmP4iARr+NwAv/1L/bAD+/vP/NADC/4gA+v9zAFcABf+5AIr/DP8GAMn/jf/M/yIA7P/+/ogA1P5FAFz/AwDQ/7D/Pf8YAJv/t/9zAHj/OwD3/joBZ/9FAML/QgA9/xb/AgHe/oEAbv9u/0f/ov+N/5T/wv/s/t7/6P8pAAz/kgDJ/8z/+v8AAJH/tP/T/3//AAB//6cAZ//AAFL/cwDh/yv/kf8UAIP/5f/Q/7UAWf/J/zAB6f67/zcAIgDz/xsAHwBq/30AAAB9AND+vAAP/z4AE/9sAHz/7/+7/v8A8P4iAIP/t//J/97/2v9S/ykAUv8fAOj/XP+5AAH//wCf/vEA3v6nAJT/kgC0/kwA3v9CAPr/oAAKACIAlgA9/wX/9/52AP7+QgCY/xsA7P/z/+L+GwH6/uH/0/9lACH/HwAtAMX/yf8fAHz/cf8tAOj/f/9QAKn/+v+U/9P/BgCR/woAL/9CAC//iwAo/y0AFv8mABP/UwADAI3/BgAF/xcBav+kAMn++v9E/3//0/+3/xsA6P94/xgAFADF/3X/n//cAEv/qwDC/woAIgCPAN7/MADYACj/XgAk/6AAu/85/ykAKQB1/0UAMv/z/5//kf+7/1AAKP9hAD3/8//M/2wARP9MAJT/3v8mALT/fQAy//P/pv/z/4b/BgBQAHj/FABeAIP/g//9/3H/0P8RAI3/wwARAGgA7/+1ALf/gQBZ/uMA9/52AEwApv9CAJv/0/+R/63/AAAy/yIAZ//9/43/BgAr/7kA/f/C/50Arf8GACkAMAC0/wYAyf9S/7IAkf+N/0IA7/+G/y0AMv+3/1cAHf9QAFL/0/+Y/7v/QP9oAOX/CP//ABb/cwB4/2EAIgBQANwAfP9vAEkAVf/h/14A8P43AI8AsP+dANP/lP+kAHj/AwDo/5T/7P/6/9r/lP8CATb/IgARADcApv/M/7v/E/96ACT/ygCt/5T/4f/F/wYAVf8NANr/YQCj/uoA8P5zAJ//5f++/64Arf8UAPb/OwCIAML/JQH9/wz/jgEP/zAARQBH/8n+vAEz/tUAov+U/z4APf/X/6AAf/9JALv/t//xAB3/SQDYACT/JQGb/6QAEQCp/5j/iABL//sAPf9JABb/GADs//P+OwBlAET/vv8XAbT+9AC0//P/CgD9/77/1/9c/30A0P7HAA0AsP+BAMn/mP83AXX/FADDANr/DQBO/1MAg/7xAAj/wwDv/5YAbADQ/6AA7//jAKL/8AGH/pkAKQCG/z4AsP9QAGP/IgCY/3j/IgAv/6L/iwCO/u0AsP9MAF4AmP8wABEAzP/a/6cAHwDC/30AHf+gAB8A8/6IAD4Akf8UAJv/aADJ/pYAfP8+AOX/vABTALIAf/+3/07/n//jAIb/MwHz/1oApv8eAUf/EQCyAC0ARP/tAJj/pwCp/+H/R/+dALT/aADh/xQAVwApALv/nQBu/2wA6P9aAAkBFv+uAET/LQA2/x8ApAD9/5H/pACK/6n/pv8k/63/UwG7/7T/hABoAOX/SQDJ/yYABgB2Ae//OwA3Adf/iwD9/1MAUwCK/8AA7P8mANr/5f8wAIr/4wD6/kUAMAAKACIAFAA+AG7/ZQCIAMn/4wBXABgA0QCw/3YAfP/z/7kAm//z/2EApv80AHMAXP+IAJT/FADxANv+AgFQAP3/AABlAMX/sgB4/y0A9v83APr/DQCrAMz/jwAmAJkA/f/a/5//pwBn/ykAXgDX/8oAMAF4/+MAR/9PAd7/vAAGACkAqwCdAF4ASQB1/9gAvv9hAP3/vABE/yYAAADT/5T/VwBL/4EA+v/RAMX/vABj/84Akf/jALwAQgBFAJkAEQBeANf/WgAUAMAATABj/5YAf/9aAPP/nQDxAO//QgCAAZv/gAFq/6QA8/9JABcB1/9FAWr/5gEr/+MAKP+yAB8AKQB9AFMAVgGj/mgAtQCN/zMBfQDs/3MAVgGi/84AlP/OAHYAXgAmAPEADQA3AGwAiAANAUT/hAGb/4QAHwCi/xEALQB2AIr/kgC+/z4A7P83AOj/EwINAHYAzgBsAIsAtQAQAd7/VwC5APgAAAA6AUIA3v+kACYAxwAo/2EBmQD9/7f/MAAJASkAXgDAACkADQHF/8cAMABhAFMAxwARAJ0AuQB1//3/aAAXAQMA7/+N/wYB1/8KACwB2AB9AJ0AGwC/AVcAKQBvAVX/egDKAKQALAE3ALUAEQDOAFcAygAmAKsA+v+rAO//fQBoAJIAYQDfAN7/vAAwAEEB1/+PAHYBnQCIAEUBYQCnAQYApAAJAZkATADAANr/4wDX/4QA1//mAEIANACPAJIAUAA3Adr/2ADKADMBzP8zAYEAfQCdAGEAXgBPAW7/jwCBACYAXgCf/2gAoABaAP8ASAH6/+0BNwCSAIQAWgHz//gA1QDKATAAIgHqAEUBMAANARABMACuAAAAEQCrANP/ZQC0/ywBu/8XATcBQgCi/yUCD/8XAcoAPgENAJwB+v9aAHkBAwDs/84A1QBeAEUA/wC3/7IA7/9L/7gBxwDjADQASAFlAEIAqwBWARcBZAHYAccAJQG1AMMAHwCZAMAA7P/OAGgA6gBaAMn/jwBTAO0AjwANAIcBSQAQAZkAYQFJAJ0AHgE+AYQA9AHjAN8AdgBCAGwALQC8AKcBGADC/+oAWf8iAVcAXgCSAPsBxf8NASYA+AAKAGgB8//cALkAjwBXAEEBwAAAAH0BLQD4AMMAjgHe//sA7QC0/4QBIgBaAYcBCQGrAO0APgDKAOYA+wCkABsAuAG8AMoAwAA7APsA5gC3/0gBVwCSAP8A/f/s/4QBiv/jAKQANwAQAdf/RQFJAK4AYQDfAKMBCgACARoC7P8QAbUAAgGyANEAUwCLAPr/lgDv/7IA4wC8ALkA6QHF/28B1QBvAej/UwGyAOoAhADtAXoAFAG8ATcAOgFlAJ0A3wD2/0kAAgGnAD3/OgHQ/+YA/f+LAZ0AVgFQAJwBsgDYAPQAUwFTAMn/gAH9/50ApACZAOH/pwBoAMAA/wCD/8oBOwBlADMBlgBzANUApAA+AQAA3wAUARcBkgB6ABQBrgDT/x4BgQCrACYAAgEAADMBRQAbAcMANwG5AA0B0QGY/64BNADtAMoAhwEiAEgBXgBMAR8AlgAbAXMAcwDfAHMAlgAbANUABgEbAMMAdgCrAIQAmQDfAH0AUACrAJkAvAD0AFoAmQDAAKAAZQDxAIEAgAFXAHoA8QBhAM4A3ACEADABiwAlAab/BgHRAKQACQH7AP8AGwBFAd8AlgCyAF0BmQD7AD4A7QCZAAkBPgCLAKAAbv/DAdP/KQFJADoB/f8GAfsAOwAQAa4A+wDqALkA+AACAUkA4wBFALwACgCjAcX/jwCLAJYAiwD7AFcAVgF6AF4ASAF6AN8AKQEwAY4BPgH/AFoBiADz/+oAaAD7AC0AAgFQALkA7P8pAUIAvAAbAG8BDQH9/1oB1QAsAasAhAAwADcBbwCBAPEAhADqAN8AgQAzARQACQGLAEwAaAH2//8A9AC3/xcB0QDtANUA/f+4AbIAKQAlAeYAiAAUAVcArgBMAMcAPgAQAdUAUwHRAG8AsQFMAHMA4wDo/+oAmQB2ALUAlgBhAOoA3wDtAB4CDQAXAWsBMwEpAI4BegCdAH0Bcf8sAZIA1QCuAEkA3AA0AIEAUAAGAccAiwD0AAkBXQFoAbIA4gGPABAB4wApAGgAKQDOAFMAbv9vAf3/VwBFAcL/nQBFAWgB6P/7AfEAUAD/AMcA+wApAVoATwGWAPQA9AARAIcBKQEiAO0AsgAbACwBnQCAAUUALAHHALkAYQCEAR8AqgGnAIQBfQAGARsAeQKU/x8AOgERAK4A6gANAJ0AjwBJAMAAt//7AD4ApADRAGwAfQHRAE8BLAGyAAYBFwEJAQUCBgHv/30BgQCSALUBTABTAXYB3ABIAUwBJgD7AA0A4wCZAO0AoADfABQBiwF2AD4BrgAzATsA1QAwANEAZ/+1Aab/8QC0/3YAfQApANgAGwEmAN8AHgERAMMApAA+AYgAygHF/y8CsP+/AZYAEAFkAWsB5gAXAQkBwv/VADcAAADKAQYATwE7ADcBHwAlAcoAfQB5AfQA+ACWAKQAgQC1AN8AdgD0AEkACQF2AIsAtQD0AEkAnQCnADMBbwBPAQ0BxwAQAR4BiwCnAPgAMwH2/4EAuQAGAT4A/wB1//8AwwBaAEUAawF6ADMCEAFrAYgA3AAGAGsBdgAwAMAAFwG8AGUABgGWAK4APgFCAGUAMwGWABABfQDOAMoAMADAACkBUAD0ANgAhAACAWQBYQBJALUAjwC8AJ0AOgEwAMMBiv9eAIsAxwC8AK4AGwDDAQAARQHKAMoAsgDmACUBAgHfAOoAzgD0AJ0AhwF2ANwAqwB9AFoAUwBTAS0AqwDYAI8AygB2ABQBEQAiAbIAzgBvAD4BwwA3ACwB5gDmAAYBMAAQATsAqgH2/2QBPgCuAB4B+wCrAFMATAB9ADMBaACnAH0A2ADmAKAB+wBsAPsAuQAiAXkBUADAACkBVgFTAN8AjwD6/6cANwC4Acn/AgEXASYASAGEAbUAVgEpAcAAUwEpADMBTAFlAGEBJQE3Afr/CQIUAHMAFAGY/64BNACyAGEBwv+1ASkBDQCuAc4AKQDHAMcANwCLAE8BbwCBAA0BuQBQAPEA7QDHAPsBUwBTAccA+wCG/0UB4wBsAO0AdgEUAXYBeQFTABcBVgFrAT4ADALM/80BXP8iAWUAiADKABEAGAC/AcL/WgDOAHoANgIUACkBvAFzAEUBzgDDAREALAHOABABtQBFAWsBY/9hASUBSQBaALIAEQCgAOMAAgE3AV4ACQG8AI4B1/+HAa4Bvv8eAZYAaACyAG8AMwHmAOoATwFQAHYBzQGA/v4B3ABsAIQATAGIAIsB3wDVAPgAhwEzAQYA4gHe/ykBMADqAMMARQG1AIQA/f+ZAWP/TAEGAZv/qgH6/7kAlgAJAZkBvACkAK4A4gHHAPQB+v+EAZIB1//DAZkA5f9nAsoAbAAeAe0AAwDjADAA8QAAAE8B7QAUAOoANwHz/7gB5gB9Aa4BMAF2AWgB4f/DAc4AsP/DAVoBu//0AZkA/f/RAB3/EwLl/08Cov8KAMMAKQBYA1L/VgEQAUwAOwDtAWwAegBvANUATAHqAN8AQgD/ABEAYQA2AnX/ZAFPAZYAkgDTAtf/cgGSANEBxf9IAe0AdgGyAKb/TwJL/3kCPQLJ/rgBCQEiAX//FwLa/7IAMAF6AKABPgCcAlMBKP9QANQBAgEtAK4BKALjAGUAHgFoAHMArf+HAkUA9ADfAPb/+ACR/2YDU/3oAhQBIgGgAH0A9ADOAJkAygEiAPsB8P42Aqn/fQEe/tsBTfz2ArUGZAK/AfMCkgBuAmv+ogI2/08Ccv7tAMYBu///APb/2ACuASIA9AFTAI4BqgEGARb/PAP+/gUCPf8yA7/+TwENARQBwv9zAJUB3AB//+gCuQDi/pECPgC8AJH/GgI6AeYApwG5ABQBlgAiAYMCqf9MAdMC5f55Al4AUwFhAEwBdgFTALv/0wNu/5kBuAGp/5UBbwGVAfQAYQGSAcoANADtATL/uAEbARoChABuAhQBkAMP/yAEUwGkAMoAWQJCAOH/iAAzAkD/tP7zAgn+agPmAPkEBgALA8X/YALv/6wDIQIB/58CJgDpAVoAwgKD/jMCcv5xA/sAxgHqAMwCUQRQ/TwDkgGIAP3/vAECAYEAfQDRAfb/1AFWAT4AyAOD/xIEpwCBAEQCPgGb/zUD8AHtAGP/IAOw/5v/WgFIAbEBE//2A50AawHNAaAAnALlAtT+rAS1AUkAswNO//gAgAG3Aj0CPASJAx4CHgLCArgBjwB4A3YBGwH+Ae0BlQEiATEE7P+nAQwCdgGdAJgC5gHo/0EBLwIGAVYB0P/xAEgB7QDmAF0BpwHVAHYAhgPT/xQBnwIlAb/+cgKt/+YA3v55Acz/sP+7//P/D/+H/osAo/7b/sL/qv7i/df/R/9q/zb/LQB8/n//7P+j/RQAiwC7/mEA5gByAY4BjgH3ATMC7QEeAY4C8wLpAfMCQwPwAdoCXQJxA3wC8wK2BIcCgQVCBdgF5QJCBfwEQAPcBYkEWAO+A6IC3wE8BJwBZwLzAhcBtQHUAVz/4gFkAc0BfP8QAlb+2v+U/wj/Nv4F//z8yv3i/c39nP5H/7H+rf58/1b+3v/N/nH/g/9O/2D/vv/Y/aP+6f3H/B/9N/3q/A39ufyx/dT91P3C/uL+Wf/M/zAA4wAKAJIBEwL0AWQCjQNfA9YDZQVQBZkFzQZMBkwGCQddBhAGmQYeBrkFygb7Ba4F+AVvBVQE1gQnAwcEjQO3AsICkQLRAbgBYQDHAKAANwA9/5T/Pf7O/En95PtY+zn62/lZ+qb6Dvuo/Cn97P6R/64Abv8wAY4BHgIsAo4ClQF5Aa4AAf8+/Vj7Y/rC+vP5XPqU+vL7uvta/a79gP7v/10BVgLWA4IE5ATrBBwFewS+A8ICogJBAh4B6QHBA9MD5AQlBw8IWAnxCuYLQQzvDRkOHA41DYcLOwonCPQFswTCAsMANwAB/8b9tf3f/Yv90f3R/TP+Bf49/mT9Ef0c/Oj6o/jg9g721ffd9uD2bvkr+ir75v2x/XX/HgGKAogFMwYaB2sHnwe1BosF7AK+/07/w/2W/Lv6QvyG+tT5afvL+9b74v0o/1oBbQMHBeYF0QaLBkwGTAXFA7MDiwG8AG8A2v/s/30ByQIcBHIHjwraDcMQbROOFZQXnhejFmkURxJwDpYK0QUMAqf93vlN97j0wPJl8g3z9PNW9BP1gvao9pb3ZvZL9fvzjvSF9/n17/Xs+cP4cfrL/GX8kv1oAHMFhwfaCIAL2g10DQMP0g5UCS4JSQrRBnoFewSmAsAAdf+n/RX7Lvua+8v7mf3K/ZX9XgDU/l3+DP83/b/9Gv83/cv8a/7b/bn8S//fAXsDewhGDm0SKBfyHOAeqiDWIswhKCDMHHcZ3BTEDu8IqgHG+VbzG+5v6QTmIuSn5E/lZ+U/59Ln7ucw6XroB+2y8tLxX/YA/P36a/3G/l3+Uv/kAyAIlwn7CzoRjRJRE/cWdxR/EjcVPhUzFcsTkBJ8Eb4NQwkmBan/Ef3G+WT4tvdP88vyiPKV7u3t7uxK67btK/DP8B70V/e1+LD6bv5ZAsYHdA40FFkcgCWdKOUrgC+ZLvgu+SywJpMi2R5uF68OSAbg+xTzDe4g5/7fSN9v3yLeFN/j3pDcX9xh3gnfT+Bb5w/rLO6F9lT3/Pbv+j/8w/3PAzkIlQu/EawXMxrNGw4e1hzfGvEefh3vHO4dSxx3GAIVZQ8ZCHYBx/wR+AX0mvI67krr/umK5Znj2uHJ4E/kk+c66pjvT/Mj97767P5HA18JGRMJG2wj+C0wNJQ2gzqROrI3FjW/L8cpziObHDETNgfy+7PxbOhk37XZvtem1jPWFtcW1xTVHtX21m3XQdro4VvnUezl9E334/dl/Hn+KQCOBtsLPREHGVofqCMaJgEnASYFJWslMyVlI4UifR/qGTgUPQxuAkv68fJ37GnoM+Ws4bXfwd0e2//YINjY2Q3eYeOj6SvwH/fq/O0BZweSC7cSwB7zJXIvHzx0QPdDckimRB1AjDy0NFwscyRuG/gPGQOF9sPpAN4X1VjOVcy+zJHMRc9F0LnOoM/jz73OINIi2kPhwedE8Hf3h/hM/esDQwQ4CqYWfh0QJUcxBzfYOMU6pzikMt8uQi1NKPYh6ByIFDgK1/9a8wvnpN571xLTUtHU0AHSFdPn02jVitZT2tPgW+j98CH6yQJfCYkOZhOjFkEalSQ+Lr0yMj+tSatHiUvKTcdCuT1SOtIsdyL6GzsPUAAl9GPm19ZxzfjFIsAlwXHDG8WTyQXMq8rwy+XLTszJ0e3abuVr7hH43AAkAycIVhE4FLscnyu1MyY9/0c8SkRJpEYRPe4y8ysfI2UZtBEXB4b6p+724VvTgcnZxNW/2MA+xc7JT9Bc1j3b2N8l5JTrM/RC/YAH2BAOGO8c0R8FIZ8hiyTLLNwzBjjKQi9JC0bHR/pE1TgfM5csuR4tFDMM6P8g8UTlQ9eByQjC1Lz1uZi8WcEDxe7J18v1yT7Ln8wizxLYwOO/7yD7YAdlD2QRIhqcJJgmtjLyQI9Gok6+VBJQN0j3PpEwtCHGFaAKyf6R9ADootv0z9jFkrujt6O3I7rhwj3M8NUr4T7ppu/k9RX7HQNBCz8UoxvoIQ8mmCaHJTckaSJrJQMt2TEfN3hApEIMP2Q+jTa0K2Al5RtwD6cFHPxu77rirdZlyTDAoLubuH66Lb8txATIoMsSzQ/M7s6i0s3a2efJ9EwA2Q5XGTUdvyTVLncySjuxSHZMVU8BVF1Om0DeNWAmXBIVBUD6fOrF4JTXOsuYweO70rW0s5i4hb8gyQLWH+Pj7cv3cf/5BOcJ3w+4Fa0c1yGKJZcnkSaLJBwj9B8BIdkohS2YMN840DqQNqY0BS+MI74cBhWzCAH/C/aH6gLf+9S2yZ/CwL9/vb2/3MTvx2jKlM1Nzo/Oa9CU1hPgpO09+iIGVhYKH3okdi5pN8I5NUbrT5FO704nUCJDczNmJwMUef4Q9DHoMtdzz9PHir1EuHi4r7SCuVfEes8e2vHoY/WY/0cI5A5BEccU4BkgHSwg/SGwIeUgeh6/G9sa3RgaG8gi/CjCKmowqzMMMPMr1ShQHvoWqhHUB7D6DvKz56LcudMNyybF2sPSxPHFpMkkzOjN2NAY1CPT7dQN3ubo1vbfAFoL2xrLIjgnsjJ3N9o6QEkET85HY0V8RJw0pCP2F74CSO9k6fbbFs0UxiXBHLo1uaS7Iby1xbLUIOHT65X4kAN8DLoT5BfMF9Ea7h1oHyYfGR3wGpoY8RTSE9oS3RIoFrwfrSX3JFcp6yyWKNcluSOWGX4TvBAQB9z3X/B350rdaNWnz+fJ38qezV/OcM5a0L7S1dQn1w7Yq9kJ39HuGv6K/nMKMyAlIGslsDZONeQ24UrMTso9KjxPPk0n6BdhEJf1quTi5BDWEMYawmHACrorvk7DLcSA0BTkze8R+EoDXQz8E/saUhzSGeIb5B1CHjcajhUnEz4Q3gxKDRYNKw0IEpAdByJ8ISUl6SmXJ1kmHySSGnAUqBPTCHL4re9N55LeOdfw0IfLbc1F0AXRds/+0GjUA9kB3BHetd+I48nvJQL7AKcFaR3PIpghODLaNXUwLULZS+M4EzBFOEcmEhMODtv4jOIJ5PXYS8dnwWPDkb1MwWrIJskg037nqPIW+pQDxgxFFVwchB82HAcdNx9zHmkZTRT6EU8QRAzUDMkMLAuCDsQYnh09G7Ef/iWBI9kjVyTOGQcUyxOgCi/6FPO+69Li2tyQ1+bPY9ED1EXUPNKd0yTXRNty38jhNOO05Y7qNvluArkARRD1I3whvSfkNmIyzTRnRBlAPi6DMA0uzBf0CwQEMOl+3TLc3suPwG3D18HyvqLIKs7U0C7iEfJB+XQDfg7pFeEcoSN3Iu4e5SAUHxgZwxUEE8QO2Av/CsMKjQjkCH4OUhYuGLgbeCEfJB8kISW1H3EXIxNUDtACZfeC8BHoh+Ci2zfUAdHP0gbU0dSS1aTZiN5p4nvmp+hE6s/rAfAX/sgDOwWzF2UjpB4bKa4zwSwmMh4+zDXpKg8wxSaLENwK3/3V4zHdtNaCyPnDn8ZgwcbBlctez67VRucz8/z8cwpCFB4b5CJUJ58lPiSPJLIePRuzGHcTYg6gC04IeQcuBBUFDgp5EQYVPxnxHtch6CE/IqIcqhbREGQMuwKZ+O/wten94Gvbw9Vw03TT9NU12LLZaN5w4qblo+rO7Wvuiu8v9CX+QgUACcIWnCCFHtQlEy8CKoUtlzZiMgMp/irWImgQYwjN/Wvkm9sZ1/HKbMW5ycfEScSizWLTLtcq6HT2BgAoDBwZTR5FJCUqfCpdJYYmQCFuGzgYaRTsDLMJqgZpBBb/4gFXBQ0LCRGjFuIaQSA2IcIgcRwxGKcQCA2IBev6LPRd7jrkoN5v2U/VOtVi2MPaBN2l4krnzuha7szws/Ck8uz0jPexAXkHdA0sGpAdWRw5JvUouyVNLU0yrimMJ8snlhkzC5IGafHH3t3c+dIkxzbMycvAxJvMwNTg097g+/PS+yUHnhiyHswhNitQLb4mOCggJ/MbkBijFpANggiDB5kB0vy0/msBugMIDQ4TqRf8HvYhyh+jH4ob0hSvDmYJav/n9/vyQepD4qHd5dbK1HvX+Nle3lnlOurL7HTwqPIs89/z6fSY9An5GgJ1B88NuhfkGNIZniI+JBMl9isoL1IqqygFJn4YHgzFAkvv1+Dp2gjRlskkzO7JIMiUzb3Tm9YB5jn1Of9wDr4c3iG5KLIuxC0lKvoqSyUkHNkYQhTdCeIG9wFU/M35A/y4/VUDmAw8ExUZ3x/6IB4gUB8TGyMUzA3tBrH+3fZK8bzo2uBW22PWa9UZ2PLcgePi6S/vPvPW9ZP3+Peh98j1HvS1+IP/NQOvCQgSnhLHFL4cRCB3IpUq0S5qK4AqCijCGyUQEAbZ8mzjTtyw0UbJscvOyYrGo8vh0trWeeVp9u0Bww+cH5EmXyyhMTgyVC2NK+klkRzbFuwR9gdSAin9P/fz9B/3n/mLADcLARJiGGsgniIOIk0ivR2HFqoQ3Qn6/9z3e/Hn50Tg9tsl1iXVcNi+3JPi8Opp8b71Qfl3/Kj71vqx+Tz2rPXI+0f/SAGeCcEN/gxhFVEdQh5PJXouAC3wKmYsBiQQFroNSP6K6uThGdhSzKjJq8lGxJXGGM871NzeuvGc/mELnxwgJx0ssjObNWoxhS2cKtQfGRjPEnsIDP8O+0j0xfDA8mr1QPpvBYwOBhU4HmEkqCPwJGkirhrOFKUOugRi+3L01Oo84nHcptbo0kvW5tnN3/jo1vCl9cH7XP85/7j+g/6O+d31FPh+/MD8JP9gBwsJkAlvFYAb7xzCJk8vJyyDK6gsFiFtE3wMcvkZ50rhfdXZyTvK/ce7wlzI2tEd14TkjvhiBLgRjCM9Kw8w8jZnNSgwMixHJs0bIxQBDZIB+/j+9P7utu0Z8e3zafsECJIQWReKIHgmxiTwJRwj1RkqFFsOZwJ9+Fjxy+fx3pzaCdaC0gHXDt2C4W3rS/Qa+cb+OQMBAzMC8QAf/Kn1zfQz+Ov2CvctAAsErAM6EOoZaBrcI8Ivky39K4Av4SbdF4ARFAHF64niW9gGyiHHVcc2wjfF1c9R1wDicfUnBBsQYCGaLLsw/DYfN/UxBCyDJYMbsREqCan/VPZ+8cjsBOzb7vXxE/nqBQcPKxdZIEonuic7KOIlhhzxFHcOuwJs90vw0+Yt3jDaHddK0tHVntzz4LjpS/U8+yUCjgdRCDAGEQV1/9z3rPFp8eTxrPEX9Ij84f/PBBMSaBqhHXcoujE9MOwvRzB2JDIX4gzY+NDlR9xJz7nEZcS3wsDAY8g/0+jb3uqc/T0MoBp1KuoylzbQOZY36i5UJ5MeTRMgCOX/7va47mDqmekM6pbtkvNT/QAKnRRuHJwlfCrKKYEoXiPWGMoQTghp/AfyuOqJ4Y7aPNhz1JvSjNi/3/Pl0/CC+5UB1weHDO0L5wkQB5v/hfaj71Lq/urB7P3rEPNe/IEAKAxFGn0fwib1Mrc1rDE8MUcrrhp7DS/+AOih2HbPrMMcv67AdsARxXjRut3z6kz9MQ/6G1kq9jV9OP45tTjqLvAk4htTEDwDY/r48gzqJ+Yj5/LnJ+y884z8jQiBFBkduCRVK2MsQilCJAwbtQ8zB1P9SvFF6XDilNtR2LfWwNQu2NTf0+Yk8Lr7rAPLCQ4PnQ95DNYJdwSY+mXyCOvK4y/ldOdV5nLvyPvmAIINrB3WIgop/DYROAgxqDH7KQUWHAqY+nvijNPFzOO/CbzCwbTBDMeJ19jj6/CkBfMWASHcLkw5KThzN3g11ShbHf4V8wcB+sbzxOxB5OPjI+fr57/uQfnRACsN9RmqH3wmKi2cKiEm0CH+FZ4JVgKk99PrK+aH4EHai9nH2VjY5NyK5fbruvWgAQQI8wwWEq4QxgyhCXkC4PeZ7hznj96s3QTicOL76B75TwGuCugcGiYvKm02jTujNCMy5CxdGpMJl/tL5VjS8crqwGy6ub/vwuXGR9bb5D/ybwXQFjUi6i0pOI84uzWMMpMnmRohEioF8vYB8C/qMeOX4kPmG+ka7076BQICC3IW8R7uI6spJSp1JpUgZxfRCpwBAvkM75PnP+NT3iTcod3B3UzfquXP7Dr0o/2qBpEMdhA5EpMPMwvKBvP+rfTg7M7j39nO2enfOuCQ5wH6fAIZCRUdcyj8KMAzbTusMYEtuCpGGP8FW/u45a3RuMtGxBC8LsN3yQjMPtp467P2PQc4Gd0iVip8NE803y7JK+Qi5xNTC/8AQfM87FPpaOQU5BDpP+1I8339dwQQC0IUVRwzIDAkmCVRIgsd0hRfCV4AmPlm8QHrA+jf42bhFORd5ALk/+i77+L0jPxDBKgJUQ7NEKkNGArtBvb/2faN8JPnz9xt2KzcLODD4yjvoP39AxEPViALJ8kqQTRfNj4ugCrLIuYQowFr9LvgIdEyzIjFlMKPycDOoNR04p7wRf08DacaryNyKsIvhC6WKZ0jeRrhDT8Ewvog8TzrNOiN5jvos+v18Uj4iv9kBngNBBOMGAcdUx9+HnsdwRh6D8MG/wBV+mD0CPC87TrqyujQ6vfqgOoN7uryafYK/KABQQbLCUgLdAm1BhIEWf8/9wfyTutm4UrcVdxB4Fjm8usz+G0DtgneFtUjHSZqK1AyiC4qKAojFhftBgD7POs621XRxc0Lye3KpdL91tzeMO42+asFUBQSHa8inSi/Kg8mYCAhG1QPggQQ/o31VOyf6mfqN+li7BXys/bg/FsEYglDDswSnxbOGdga6hlfGL4S7QqIBY4Bgvvq9wv20vLp7+jwFfFS7wXwWvPe9J33nfw5/+0B6gVTBu8DHQNkAaj7GPft81jseeSA4LrdoeLm6anrI/ZxA+YGvxFbIlMkEyUML/gtvSPlICkaagjZ/E/zbeIz1mHVp8/9zBDWuNo+3ufs9/nMAlsPERkEHR0hOiW7IdQbvRjgDqIDQP/H9/Ht7uyB7ZzqwO3780n30vzBBH8IIQz7ENITZBbZGAAY4hZCFH8NaghhBe//TfzI+nr3n/Tl9I70mfPc8tTzmPRx9Tf4OPt5/RABkQKEAV0BhABv/fv4+fWJ8b/qw+TI4S3jHunL7HTx/v3ZBPIJoRhtInwgrSb1LQgmiiDnHoARWAO9+3ftp94+2QLW5tDD1OXb1t0o5Sz0fvwJBtcRtxfRGrggdSAMHF8Y1hLUB5kBmvwz9G/ug+867qHtzvL19tT5oAFvBpMJhg0FEagTyBcEGI0X8BYkEooM9Qn5BC0AQf6v+w34pfZ79ij1BfS28qjyffOQ9e73K/pn/jABrgC8AaMBOf9+/L/5VPZx8N/pjuWC4WjkCOvR7fP0EwJ2BpAONR01IgciECpOLF4kjiD6G8YMhwGy9xvpHtsx2MDTXdCs1wfdPt+f6gf3L/+LClsUVBgjHTYhHx+8GigXDg/yBC0AwvkS8dTuLO/A7WPwCPUi+D79qAScB64LaQ8yEuAUPBiJF/4WwxWOEHYLUQknBNf/o/5Q/FP4zvd39/n1bvRd9CX0lfS29oD5yPoW/0wBLQCSAV0CVf9X/FT7k/dt8dLsJuip4K/io+lG7Pnx/f+dBbwKqBlwIqofUiZcLHYkhB+dHhARTQS5/CjvNuCO2o3XbdJH167ebuD158H14/xkBuIQMBU/GG0dgxy2GRAW8Q+jBiwBl/vQ9OXv8vDs793xg/Wj+ZL9cAS0B4cLKg6jENYS8xa0FjkXnxbdE00OhwuZBvsBYP/+/cL5lvdC9xX2KPQQ81Dyc/L787b28PhX/UwAQQHMAkcDVgHC/rL8/vka9Sjw+evJ5UXjneiv7WrwjfoVBP0IWBKTHgUgLyFNJ1kmcB5PG2IUowZk/WvzreVA3JLZhtbM14jehOPg5//yYvw7BRkOOxQMFygbRBtlGX0VWhD6BywCJvwR93TxIPGp8HfyVfWO+I/8nwK8BsQJJA31Do8PaROLFVQUqBTcFLkPIQxJCsAFoAE+AUj+ivre+Rr5A/fd9Sj0tfMM9Dn1svdZ+u39OwD0ACgCtALKAA//A/0W+hP1bfDd6w/mLuI15nvrmO/n9zwDbQlMECgbtCBhH7kjrSZ+Hl0aBRc4Cm7/OPfz6lbfhttv2uPYFN4L5hDpVfAq/AEDWAkFEWIUqhW6F/4WwRJRDoUJrQLx/B75gPSF8ePyMvVK9nz5QP/vAhAHKgrJDB0NHw/JEboTjBOaFCoUoBCjDNkJsgU9AlAAgP5R+9T5rvjc97f1v/OL8wL0h/T890P7bv6qAYIDIAQgBLcCxf+q/aX7ofbE8X3u+edR4hHj4eYT63vxIv3cBUQMwhbpH+kfbiFLJTYgbxroF1sOewN0+wvxY+YR3pDcfdpH3CnkMOmF7WT5MAHzB/kOohJKE/sUMRTdEqkNHAqTBJH+8/nP9hnxDvEb8/r0fveg/a4BoAbSCTkNSg1ADScOSBFIEUAS8hNRE7oOBQ26CRwFTAFoAX39jfq3+vf5tvfZ9nz18PPp8xn21fdx+kD/tQGwAsgEFQQXAYgAa/60+YP1B/LF66zmyuN04VrkQ+sa8N75YQVEDCATuh3iILEf4yMOI5gb9hdHEu0FpPxu9Jnpo+CB3oncBNxU4mnonusW9Y7+xQMRCqEPsg+jEQsTmRCtDMAKvAWZAGn8nPkJ9LLyn/Tr9Yj3Kf0zAQcFcQgJC5YKMwtFC1kMlA0KD0EQaxHqD/INGgwOCRAG6wSOAlX/qv1l/ML5G/is9dTz0vJB8/70d/fT+s3+IgHsAioEDwMQAgkBgP5q+kb27/CX6wjmg+Co3S7hk+fE7Kv3AAUQCzwTZyDSIuwgBSb3JHgcshkcFKAGpv4H9hTpfd/a3B/ZyNga4KLmOurX9Mb+vgNUCiYPqA6YEUoSWw8ZDSULPgXM/7376/Z38RLxVPIM9EX4jv2/AWEGKgrcCs0LQQzjCqAK4gvXDGMNIw90DhcMEAu2Cd8GaAUOBSgCiwARAFf9m/q/+HX1qvOn8zPzqvQU+BX7//wd/44BOgEbAe8C+wHp/az7d/cu8fnr/eX13fjZ+N6A5QzqzPVxA2kJsRFkH1Qi9R5LJT8nCh54HM8XhQnKAdj4fOoo4MLbStcn1z7eCeWg6NnxpfswASgHHgzUDDoQtBFFEL0O3wuLBUIAe/vB9Z7xse+e8Db0YfiF/GQBsgXoCD8KigxnDAIL7QqcCzcLOgxtDUsMQQt2Cz8KXAjhB+EHxwXoAwQD6P8n+2j4pfU/8i7xdPBj8MPzafZ9+Ar8Z/+ZAFkCHwXfBQQDPgGO/lD3WPDU6hLiiNky1+vcB+OB6P31QwOiCL4S8CAnIoog0ihhKQIgwB7IGMEIvAAO923nPNww2UjVAtWF3TDk2uYZ8Tv8kgCcBrcNJw70ELYTchGiDYEKiQSH/dX33/Ma7+Ts/u8e9E33W/wzAn0GZgmHDL0OLg5ODesNmAzDC5gMgwySCmwKsgoHCXwH2gdkB8sEXwMeAmv+n/pI+Lr1YvJi8VzwE/BI87r1OPf1+0v/t/8eAtYEhQQCAkUB6vze9P7vS+p54KPa3NiN273ieeoS9lIC9ApCFGcgxCPsIVgnOyg2IEscSBYLCCH/XPXn5w7dBNg61VPVhtyB43vnkPD8+3YBvwaeDSAOmg/zEZ0PqguXCDkDnfyd9yH0mO8R7ZTwg/R+9zf9wQMsB7UKgg7YD6wOAA45DTsK3gebCKYHLQVSB0YJhwcyCI8KqAnXB40IlQY2Apj/xPuy91n1afHR7vvugO978CXzevf5+tH97QHWBP8F3wZMBm4Cp/1p94rvkOdd4GzZG9Se2Fzhm+ZN8eYBegqxEYcgySYYJKgoaS1+IzwdsRrYCuL+Qvdp6CzaNta201nRQ9js4NjkhO4H+6AAAgcODw4P5hCQE98PtQs8CRkDgvur96Hyoe1U7envpPJr+Bb/ZgSFCTQPPRFHEqISoBDhDUwL8AYgA9EB9v+0/n0BYwMxBMIHuAuqCxcMXw0mCjMG1gMQ/lr4XPU18Q7tBOwZ7HvsgO519Lj4B/xSAlUIywlaCzoMuAdhAfb61vGQ57Le3tau0C3UtNum4Lrs6f1oBrUPWSBCKOQnwy5QM1ApaCSZHwcOgwJJ9zbladiT03TN5cua0+ba3uA87Lz4OwBUCSERXBKnFfMWDBLyDkULIQLI+qX21O+z6wvsiO0j8YT4Uv8tBYcMcRJlFMkWWRelE3IQNQ0JBqb/A/zV9271Yfh7++z+kwT4ClgOUhF+E74SMxAXDJIGCgA5+hf01e3U6RnnVuUx57rrK/C29uL+wwYMDI4QhRP3EdoNTggX/nDyJuhp3VrU9s0WzNrRo9pQ4wn0RwNHDVkchSx4MO4xZDmRNCkpNyR5FsICQveu6KzXss77yv3HAstu1h7f1uZb9nED0glfE9kZFRg/Gd4Wjw8SCeEC6flF84DuzepP6TLravCT99T+1AfHDx4WRRq0HCEc4BgnEwENAAX8+8j1t/Bb7CXuqPI49wj/wQiBD0gVFxuwHOkaRhjzEYwJOgE++Brv5Ofy4oDf3N6l4gPoMO5y+E4DhAsuE+oZUhsAGR4Vawwh/4zyFua22MDOf8f6wUvHINJ82xnsFwGCDuEc0DA2OmE5YT4IP/4vNibUG9MDkfRN6CHW58lxx1TE5sXI0vzdkOba9WgFKw1BFuAdFxsfGi4Ydw5oBhsBvfbD7u7scumz523ryPG8+BMCfAxGFGEaYR/QIKEehBqMExEKUwE++KPvjuly5Y7l/upG8tn71AebEvcabSJqJtsktCAwGg0QxAR8+V3uquW13lLbo9qK24nipupd9OYAUQ3KFeQdMSO0IfkcchU1CUT5UuqY25DNI8Rcvam4pL9mzR7atu19BgcYHSepOutFgEPRQ7hDnTI3JDEYGv8b7ufijtDHxCTD/8C9xFHSzd8d6/r5GApbE5kaTyALHd0YhBU7Cu0AjPtl8pDr0OpP6TfpRe499YT9DwjQEagZuB8qI5Aidh+IGdUPugRf+4zx7ejq45zgeeAL53HwzPrzB28VTB/nJ00tZiwqKL8g2xXrCJ77uO5z43TdBtmY1jvZi98j57rxg/5oCxcWxx6AJZgloiFrG2UPGABH8AbfZc//xE69ZLfit8e/8c5/4RD0nwzJIckwVT/SSwBLh0PvQKo08R7RD2v9r+ck3JzQy8QlwevDwMmC0sviAPEc+68JUhavGW4cLh3HFJMP+gdM/bb28vHo6wHrEe0h7+Lz2vrPA8IM+xSGHNQg5SETIZ8caBXRCzcAEvbH7Xnll+EL4YfgC+by8Fj7vAYQFQghTShzLrQv2ypQI7kZcgyD/knyyOZF3orbN9md2crfr+ex7xz71AcBEosaHCI+JPAgkRyQE34EFfZK5jPV4cgXwVC7A7qCvjbHlNca6738ghLOKCA21z8nS8FKBEBxOggwPxjhB3n5QeSI2SvStMfVxDvKJs8o1szmBfSB/DgJqBRkFhUYehlBENUKaAV4+j30pPIs7jvtDvLM9VL6tQBpCfsQ/hYSHW4gch+eHfUYlRBkBxT9ZfLe6mjkXOGQ4dbiYudV8I36tQV4EqEexCd3LZ8vCi7sJtYcGhKEBQ73AOyk48XcAtsL3Dfe0eTr7Hz1fQDpC2IU1BuHIDogzxwBFxcMnP1I7+3fS9Hsxx3C+b4GwTDGLs713VLwiAB5Ff4qxTVMPoRIGEc/POE1zSrPE9YERven46DaU9Uiy2nJx85c0cjYI+g+8xj8nAcFEQoURBYoFroOZQo4BIP69vXJ9JPx5/Ex92f6SP7BBDcLCRHwFnkb7xxSHP8ZVxQnDcgEvvoc8Vbq4uQO48DjleUl6jTyjfq6BAkRfBuBJNcrZS7SLEkoDCAeFdYJ1fxV8FHniuD83VDe1d7R5FzrofED/OoFQw3iFUQbrRtFGlkWgg2xAXX1iecK2avPQsmFxArF/chKznvYc+hP+boJDh6LLlA3lT7CRFVAhjXVLRAg/wo9/ujwxeDV2dzT5cyGzU7RR9YX3zjsxPf9/9YJ2xEYFH4UmhO/DG4HGwG7+ev22vUo9Dj2Tvq4/YMCbgeCDT8T/hYRGmAbFRmqFeoPSgheAL322O376PDkp+Ps5QLp+O1V9bH9JAj5EpEcbiXoK4wtKyxYJ9keRhSbCDH8JPA451XhG9593tvf6uMX6sXw4vkuA4sKnhI4GDgZkxi8FegNqQP196bqz90803jMMsjCxzDLFNDd15Tm4PaABvkYZCrAMxY6okDMP2o17yuRIb4N4v778q7jsdpE1jfQ3M5t0rrX3N4163f3AwD2B7wQDhRUFBEU+Q1HCLQC4fp09gD2EPTe9Lj5Xv2ZAdQGeQzpESUW8hgiGoUYbxUCEBIJ4gGH+IPvXerU5f/jIOYQ6Vft3vS2/IsFLBHmGusiYCppLakrrCcFIaMWBguG/+7yKujT4YLdQ9xG3R3heObr7Hv2EQA6B0wQghfWGCYZCxghETII/v1N8d/jmthM0GHKnsgly0zP2NVB4PTuKP8HD9Ef4C1ENWs5FD2gOHsscCMFFyAEx/c/7ALfltns1szSH9RM2WHfmuff8xP+BAQ3C24RuBHNEBEPwgeAAjf9WPZE9Fb0E/TZ9z79HgGuBhcM8BD7Fa8Y4xk/GdEVCRFzClwDvfuB8qzrvec35P7k7egx7FvyqfpuApUM9xZbHrglzSoCKrQmnyHZGM8NbQMG+AfsDeS839bck92t4ObkTuss8wf8KgSnC1ETYBe+F6oWFROuC4oClvdV60zf/9TSzq7KJsq+zevSVtoO5w72+QQeFRMl3y4CNHo44zg9MNMmJh4xDnX+sfQt6F7emNul13bV59ha3mHk5u1L+UIAbwWVDFAPCw4ZDXsJrQKR/vD4ivR59Nv0tvbS+7kAiAXcCqgPyxThF0IZjxm/FhMSjgw+BRP+Q/YN7uro6OWc5ADnBeuj78/2Wv0ZBCsNhBVjHJoiwiZqJusiER7sFsIMHgJv+I/tQ+bP4l3ffOBy5MHmHOwo9JH6eQEZCWIPOBNwFEYUgxFWC4IDLPnH7fniItna0YLN6Myrz73Tudlz4/fvpv6zDQ8c3CjzL5Yz5za8M70oDCDGFbYEM/mf78rjM9+a3erY7dkl36zi/+jm8+T6df/YBcoKFAvcCqEJugPe/yP8wfai9b33F/my/LQCCQcXC7UPhROuFYcWgxYRFJ0PHgulBPT94PfT8JzqrOcu5kbnf+vz71z1q/z9AnQIxw/lFlYbyx5gITMg/hvTF6MRhghL/8T2Xe7D6Ljl8eOV5a7oAev37zX2P/v7APAG3wqUDd0ORg4XDNAHTAGE+Czvceaz3ZHWgtPP0rLThtc43djjDO+E/TsKpha5I/cqMC5NMpcx1ieOH2kYCwma/K30oOnE4l/hcdwv2wbfW+I85/7v6/Zf+28ALAbzBwgIiQg7BYsBzP/E+8n5tvwF/nj/7gQrCI8KVA4FEVwSxRLwEbIPbwsCBxoCcPxQ9ybyveyR6gzq5erK7pbyrPYt/WsC5gVaCzYRDRUHGAwbqhs4GXIWGRNuDDEEa/0q9pXvaezN6Sbog+pq69bsk/H59eL58P66A3UH2QmjCwIMvQnHBdP/4Pf37/LnvN+/2qLXzNYV2N/aMN/v5XHwDf1YCY4VEiIwKVcu/DG/L68nLyDCFkMJw/0X9I7qAuU84Rzd2txo3nvh0+av7afzVvni/pAECAhYCawJuAdhBbQCTv9k/ln/6P8MApIFyQdCCgENLg7yDtIOag0lC7QHIwQmANL74Pe886PvjO0m7UXut/Di8yL4A/1BAQoF3QjiDPcQ2RODFjEYlxf3FawTCg9HCMMBRvvN9DbwYuyu6ffpAurp6inu7vEE9tb6pv/yA5gHmQooDOILkAn5BJX+afcC71zmyt/m2uvXxdcD2QvcWOFM6aL1JQLrDW4bOSbXKzkwbDKMLb8kNR2NEsgDyflc8MzmP+Ii3zbbJ9yZ393ikuii8JD25/vzAkAIsgoQDBMMfwixBk4DFv8F/5j/Gv+OAboEOgYuCYcLhwwyDb8MHgsgCSIG/QI2/8j7mfj+823wee9h7jrvXvKH9BH4Yf0bAe8DvwclC18OuxHHFJEWGheqFtIUpxAQC1gEh/2F9+fxtuyZ6fjoW+gN6aHsBfB580/5Nv4MAlYHQQviDMUNkQwnCEsCqPsC847pk+LP3K/Ys9el2IrbxeCQ56XxAf/jClYWryONK5IueDFOMTQowB4hF7MIWfrg8ovoqeDf38/c0doC31DjvuZT7qj2ofslAZsIpwtSDM8NlQuVB6AFHgGA/RD+Bf4J/rEBfgTmBvwJvAv+DOUM1AtNClIHFQTjAEX9Pfp+9lvyQPAa733uhvAl83/1YPod/xMC+wX8CdYN0BHtFEsXDhgdFykV8BFkDK4FK/+/+Ofy6u0l6qfop+jq6FjrQe/x8uD3w/1gAr8GGwvFDYwO/Q2rCucEwv5U90HuouYI4Vjc49la2jzcZ+B55dLs/PfIA1EOoxp4JvAqry3QLycsIyIDGloQgAEq95/vSuaQ4hzip96L32Tk7+bX6k/zCfmV/d0DBwnHCtQLWQx/CO0FPANZ/p38oP2j/QX/NQP/BZsIjgvJDCANjgzKCmYIegVBAqb+r/sX+Uf1DvLv8I7vo+938q30Kvdw/LIAQwMJB3YKCA1IEDgTqxSVFUgV5BM2EdQMDAfOADX7Z/W/7wTsF+qu6Gvpuutk7jTyTfdN/NEArgUVCrsMWw41DjcL3wauAT36HPIP67jk2N9m3XTcjN2t4FLlWOuY9FcA/wovFm0iwCgTKwYuKyyvI1Ib9xE4Bf75HPIC6tHkeuND4fPgSOQ155zqjPEK+IH8JQJWB70JnAv7C34JdgYLBLf/6vxF/YD9df7wATsFmAdlCksM0AxPDO0KmwjHBbcCdf+P/Nf5pfaZ87bxY/Ar8CryXfR79sX6Mv9SAqsFBAmcC1gOSBFbExgUlhQDFN4RoQ4qCnsE7P6j+Qz0M+/56zPqw+nb6vnsUvBB9ET5a/7FApgHjguzDXcOcQ1JCu0FQgCA+Tjynuvs5Z7h3N4H3lbf6+KX5//t8vYzAsYMfxcjIj8nvClAK6Eo+iAgGCYPQwSV+R/yXOs85srkoONJ45/l7eis7ODy+/ix/XkCnAazCd8KfQq6CBQGfwMUAKf9uP1S/mP/gAJ9BbgHKgq4C/cLZAu9CZUHBwW4AQz/KvxP+fn2qvRe8qHxRvKc85v1H/jk+5T/yQIpBsgIaQovDLMOLBDbEOURuhKAEUYPLwycB08CYf3j9w7yQe6z6wXqLuvW7MPuBvMm+HD8MwH0BREKLg2oDmkOzQyzCS0F7P5B+HDxn+qV5eHhhN9M3y7h5uRB6qLwGvqPBdgP6hn8IuwmUyloKY4lcB1zFAkMKQFG9zXx3uqG5tTlzeTp5KjnR+t172717/r+/psDCwhJCosKwwpKCCoF1wIo/y39p/09/r7/JwN9BegHhApoC28LoAroCLwGxQNTAWT+YvvC+XD3g/Sg82vzMPP39F73Cfn1/BAB6AMsB+sJ8QqxC04N6w3TDQAPAhAKD3sN2wtVCDEEbwBD+5v10vGH7iDsnuwG7mfvT/Mi+LP7LQAKBQcJ/gsSDl8OXw2ZCyAI8wIK/W32Nu9B6Uzk5eDt38HhruTA6DDu3fXQ/nQJdBNgGwQi5SXlJuwlfyHgGXwR/Qiq/n/1n+956hXnlOYd5uvm++mO7qvySPgY/ZYAxAT6B54JywmzCc0HGAUaAn//Cf77/QH/bAC+AmEFgwdpCYQKpArSCVEI3wU1AzsA0f2v+6r5iPfT9d70GvXP9fz23/hb+z3+dgGMBEQHPwmgClYLrgtPDM0MIA35DX8NhwuzCZ8HCwRTAC38tve186zw++6E7hPwEfJO9Vn5Xv1hAfgF0gmADM8N4Q36DMcKTweVAgb9cPea8azrd+fN5MPjquRY5+nqse4J9HD7lAPKC4wT7hk3H9MhDiKYIJscfRW6DUUG4Pyb9azwWOzt6VPp5uj+6Unt0/BW9B75MP0bALoDsQZACDgJPwlWB4sFdAOyAPb/4f/X/98AuwJRBCUGzQelCNYIJwiqBpoEbgJJAET+bPzP+gX5q/cx9zH37vfw+Bb6z/tg/gIBlANdBkcIWAmQCQ4KiArRCn0LZwyDDGgLTQrBCP8FogKK/vD5g/Xg8Y7vGu8o8CbyS/Vk+af9AgJkBgcKmAy6DZANkQyBCmAHYwOR/l35xvOg7nXquueG5v3m6uj560/vKfOH+AAAjgYZDVcU2RmNHMAeTB9nHPAWZBEfCrEBGftL9VzwFO5U7AjrsOv/7RrwM/Mm93H6V/2rAMwDHgYZCI0I8wclB/wESAJWAYEAt/8tACIBjgKaBCwGigdjCBYIIQfABboDpwF//9/9NPyU+ln5qvg++PD4jvmx+f36//zz/m8BHARBBqYHXAhcCHIHfQZ9BhMH5QepCMsJZQp2Ct0JgwcnBLv/8vo89sfyuvA58LrxrfSy9+f7uQB3BPoHLQoGC2EL+AqFCaoHHwWVAY79DPmf9MLvfuzJ6pnpOupw7O3uMfKF9pj6cf92BUEL3w83FZcYZRkYGl4ZIhVbD3oK2gN6/Mf3hPN57xfuyu1i7VnvDvIX9C331voK/ZT/0wIYBYcGowfJB4cG8QX9A/sBAgFlAHH/+v8+AXICAASdBbEGGgfpBvEFXwSYAmgAPf7A/Hf7DPqD+Y75nPka+vb6nvv8/Bb/2AC3AqEEJQbNBhoH8AY6BsMF4wV2BhMH7AfFCDUJMQn6B4QFOgJ1/jL6rPZS9BvzQfNL9fj3HPsv/9cC8QVKCKUJ2QmeCakI9wazBAUC5f4O+4X3DPSp8PTuG+5w7bXuIPHV8i/1fvdS+Yv9GgIwBrgLgBHLEwIWOxkcGJMTDBEQDEMEnP60+Z/0I/Lv8HXvS+9f8QrydvPg9jr5bvrU/SUBMgNWBuwHVQgACVkHdAQZAx4B7P4J/jP+yf5FACgCOATRBeIGDAcCBsQE0AI3ANv+w/1J/Dz7Rvut+uj6NfsE+1v7j/yq/df+AgH6Am0EvAXDBlYG/AToAwsDPQI2AkcDyARBBy4J4AkmCugIBgYXAmD+NvqM9uz0u/RH9WX3vvoT/pIBQwT0BQUHuwd5B4QGnQVwBI4CdgDm/Y36r/e49ADyePAT8DnwFfLp9CP3Rfg9+bD6ZP0+ABkDcgdLDHQOEBHmFPQUHRJoEIMMkgXQ/6z76/Yh9Nzy6PDI8KTycvOx9NL3sfnW+mj9EQBdAg4F2Aa/B0AI4gY/BKkClgDG/TH89fvr+w39Wf/KARkELAYaB9QG+AWoBIoCAgGi/9H9afy2+2L7hfu2+6H75Pti/MD8cv0P/6sA/gFmA5AEqAQSBDUD9wG5AC0AXgA2AvkEgAcDCsYL8AtlCpEH6AM2/4364PaO9HnzSPTu9nH69P24AawEbwb6BxkIfAe4BmwFngPRAYP/ufzX+ev29/NR8Rrwo+/+70ny2/T59mT5sPoc/Pf+mQGlAy8HKQutDKEOzREyEv8PIA64C5IFnQDg/Pv4m/V89IHyMfKx89f02vVW+LD6OPvc/Gf/bwBZAiME3QQABTQFmAJvAYsAOv6r/I/8wPx9/VL/owHWA7IF/gZLB+0GzgUEBPABnQBy/k38nvsg++H6Lvtb+1v7tvtw/JP8xv0T/14AKQFnAuECawIvAv4BcgE3AU8CngPxBX8IHAr0CkwLxAmHBicDDP+D+jH3OfUJ9Aj1W/ef+sn+LwIfBToHsAjTCMIHZAaQBBACsP/x/Nv5gfc59dXyxPEc8Zrx+/I59fX3Ifqo+xv9p/1n/gYAAgKUA/4G0glBC9YNoQ9wD2YNcgtKCDIDRP9U/Mr4uvZH9f7zM/TJ9IP1bfY++Kb5Gvpw/JX+hABgAq8E5wQqBeAEawKZASIAEP47/Sn9gP2O/oEA7ALEBEgGBQc2B1YG2QQPAx4BeP83/ev7Tfup+rD6t/rk+qb6mvsK/KH8KP54/50AhwHeAuwCjgKKAiwCuAHfARYDZgSLBpsIuglzCnMKbQinBZgCn/7T+kj4ofbh9Qf3KPk0/Gf/TwKlBEgGSwffBq4FUQRyAvb/xv1R+/v4OPc59T301PP780T1NPdy+TH7c/yq/bH9A/3H/Ej+g/8CAXAENQjLCY4MgQ+uD2YNMwxYCbcDgQAG/Rr5B/eU9fDzp/O/9GD1lPUD+GT5FvrO/Ir/PgEZBOoF9AXDBv8F9gIzAlMA0f1w/FT8xPyL/f3/qQKQBGQGnwejB9EGmQVtA1MBfP8U/cH77/pq+kv6sPrC+u/6Efyv/EL95f5FAGsBSAKXA5QDHQOAAhsBRP/N/UH+Wf8+AVcF4Qh9C4UOuQ9NDiUMtwgSA/D9h/k99X3zCfTs9Lb3nvu4/jYC1gQsBsMGEAYfBScDNwGf/179H/w8+zP5M/h2+JP3Rfjl+ev6G/3U/rf/pABx/+b9tvxU+z/7vfv8/N8A4QOLBv8KGQ7WDfYNYw04CQ4FRAK//dT5Kfhx9bT0TvUS9n72Bvg5+u/62fxj/0wBFgNFBToGDQYpBkoEZwKdADr+MfwO+/n6CvxM/VAAQAPABRIIFQkxCVUIygboA7UBPf+2/Jf7lPo5+hb60/p0+zH8aP0M/ij/LQBrAcoBZwIIA4AC7QHxAK3/jv7b/rv/YQEcBTwI+ArEDikQeg+FDoQLkgaZAc78FPiG9WT0ivSM9oD5/PyLALMDJQZrB4MHFwd6BVEDSAHQ/hT9Tfuc+eb4VvhF+Cz5CPqh++b9Y/+uAZQDiQNfA3kBDP5Y+wn5aPiu+Dn6ZP4zAnYF7QoHD2wP5g/DDxcL1AYnA/P+Wfo++PL1fPT39A72I/YK+Kn60/o+/ZkAmQFmBK4G1AZdByUHTQTXAkEBAv4m/G374fq2+7X9zgDoA4QGOAkDCkkKRgmDBw4FqQK0/wP9xPs2+sn5K/qU+kb7ZfzD/Sj+YP+rAD4BwwGHAskCWQJBAsYB2ABCAH0AGgJmBCwHnQp7DfgP/hA6EHsOXQtaBiUBc/yo95z02/M29Cr2OvnE/LIAKgSHBg8IdAgPCFoG6wPNAVL/Lf26+1L6jvmY+ff5Kvsi/eL+MAGJA6AFKAdyBzoHKgVIAQP9k/c+87bxafFi8uD2MP3UAcEI2A+CE3AUSBUxE/AMMggrA479+/iX9nnz0vJB9Br1ifa0+UL8rv03AQ4EUAXXB8UIyAjhBxcG5QKZAP792vrf+JX4EPkL+0j+igIsBrMJwgxODZQN2wttCRcGawKY/hL7YPkb+Of3jvjJ+Yn7Pv0r/0UA2wHvAoIDzwObA2oDjgIJAlYB1QCgAbsC7gQHCYALog3YEP4RYRDLDr8LQQZhAdn7gfcl9IXyHvNA9WH4bPyyAHQEiQjuCcoK+wrvCCUHqQM0ABP+Nfsv+dH4Efi8+P36Sfxn/2sC/QPfBqUImwiNCHIGNQOm/wz6yfQf8rfwpfCH8474Uv5UBDcLEBGMFN8VpBRREqYMsQZvAUL8hffb9KHybPL381j2ffjr+8X/owG2BKYHXAihCW0JcQh9Br4DCgC4/Rz7WviW95r3BfkY/G7/0wPvBx4Lzw1RDhIO+wsgCW8FhwGL/Sj6ZPir9wb4+/jo+m/9cf/GAR0DPATrBK8EDgTzAv4BmQB4/wX/K/+t/7EB7gR7CLULgg5IEUcSQRE0D78LvAZMAR/8q/c69NXyWvNS9bX4ufz0AEwFFQm1CtELnAuMCQUHRwN8/378mPmv9/X26/YN+JT6GP2BAPIDbwbaCAkL7QqaCewHAAXT/1T7LvZt8b/u7e1r79zy1fdH/+oF9AsvEsoVqhUlFSsSSAswBnoA+fpN9rXzEfKa8oP06ve0+un+igK9BGsHQwmJCBUJ1wf8BHkCav/E+4P52fdp9iP21fdE+jf9eQGyBXsJXQyFDokO6A1BC1wImgQ+AIX8n/ki+J33+Pet+cv7Ov7KALsC7wPEBNkE0wN8AuMAJP+q/dL8EfzP+2/99v8PA4cH9wuBD7ASxxRwFDISHw/1CeEDv/0z+M3zgvEE8ULyjfVy+ZX+XwNrB3oK9AsMDLwK+gd+BJ0A9fwP+oz3APYH9u729/jZ++L+cgLYBScIPwp5C6sKOAnYBh0Dkf64+ff0ePBJ7b7rmu2i8Hj1+Pz9A9YJ9xAiFQUWeRULEx0NEwcGAYX7DvbH8iPyyPHp8yn4d/t4/9MDzgVuBxUJ7wfUBjsF7QEy/zT8SPlG93v2B/Z79mH4vvpv/WsB+QRfCAYLzQx0DfAM5goPCMsExwAw/UT6Qfhs96v3Nvkx+6r9dgByAgQEvQSMBDIDvwGm/3b9l/t/+vD5xvlY++b9oAFPBhsLaQ/FEr0UFxViEyIQNws7BdT+DPko9PLwFvDd8G/zVPc7/CUBbwX9CPsKawtsCkoIHwVkAdH9cfqk9/31XPXT9U334vmF/HX/yQK5BTII/AkJC8cKWAnmBqUDrf8g+6z2TfIC7ivrwurW7Dbws/Wg/S4ExAmEEDgUFRQ/E9gQVAoVBAH/lfkB9Zzz9PKq83r3afux/u8CtQWLBigHzQasBN4CUwA0/fn6ffhi9uT1PPZ+9oj3yfng+1n+vAHEBK0H7gmAC6ALBgsuCYAGogNeAO78YPoJ+W/48PjF+sT8RP+qAV8DKgQZBC4DWgHp/nD8kfrK+Ar4aPj7+Lf6+/0oAsoGaAuID8wSXhSFFOsS0Q8eC4EFOf9n+bH0SvGN8DzxdvNQ97r7iACzBLQHdwndCaIIMAbXAhP/rPtI+AD21PRr9LP16vfP+hD+TwFmBBcHWwl6CosKBwonCNkE7QHm/a35r/bZ8i/vc+1b7MPtafGs9dL7nAJgB08MSBDbELIPiQ0LCeUCvP1n+fn1IfRS9Jv1Cfkf/RsBtgSKB1gIJAgvB5MEUwG7/jj7N/hf9pj00fMo9X724/c9+sv8If/bAUYEoAZmCCAJWwmzCBcH9QTQAmgAyv2e+7T6ivox+9n88P4QAUADqAQfBWYEBAPDANH92vpI+D/2R/Wb9aj2sfgt/LUA3AW5CiYPpRKFFNUUURNhEPcLlQbcACD7bfYp8+DxiPJL9F73P/uG/zIDFAbNBzwIXQc7BUgCxv5i+474Q/YF9ar0l/Xg94r6zf1aAYwESAfkCSwLOgvDCu8IFAb6AmP/r/vG+Cr2a/Oa8Y3wmO8F8E3yS/VI+G/9VgI7Bb4I9wtBDEELCgqVBj0C1P47/Mb5p/h1+bT6TP3fAF8DXgUlB+IGegW3A8MAlf3a+uf3z/Xi9ET0zfTL9oD4D/p+/LH+PgA2Au8DSQVaBs0G5gaSBsAFswSQAxcCkgBE/9f+xv7w/u//+AD+AewCDwNyAkgBjf9M/d36i/jL9sH1sPWe9j74kfqn/SkBAwW6CAkM+Q4XEfoRqhFrEDgOygqnBmsCVv6w+jD49faX9h/34vhD+7/9FAACAisDQwN8ArwAn/6P/LT6L/mA+Gv4KPnW+hv9m//7ATgENwZSB94H9gdEBzcGngTFAsMAtP7j/HT7T/nL95D2qvQz837yofKL87r1GvnS/GgA9gPGB7YJcwofCv0IGwZKA8MAiv78/IH8GP1k/nYAdQLvA9kEywSNA+IB+v9k/fb6AvlQ9372IPZt9r33L/lq+uv7gP2m/gYA0QFRA7YE5gXbBmcHowdLB7EGygWFBCcD9wE+AcoAqwAiAYcBzQHbAYQBYQDX/ib9APsT+Yz3uvZ+9hz3qvim+jT9BgAZAyUG9ggwCxINmg7uDucOiQ7UDKcKXAhFBVYChv9C/b37g/r6+T36+foO/Gj9g/5//9P/m/8W/wn+Lf07/Jr7gvuo+4j85v1n/yUB7AI/BH0FWgaVBmsG+AVaBRkE5QK4AUIAHf+n/VD8NfuA+Sn46/b39Gvzc/JQ8mTzMvU++IX8VwDkAzwIvAr0C3IM1AtUCdgGWAQJAhEAOf+m/gj/GADYAHYB6QGqAasAhv8Q/kn85PqY+dj4jvhB+Kr4lfmG+iP7O/x2/Zz+UwAMAgcE9AWYBwAJ/AleCgMKjAlcCJUG1gQSA9sBtQAbANf/tP/Q/1L/9/4e/g39/PvT+tD59/jG+BP5BfqF+yL9XP+LAboDuQWqB7oJTwveDC4Orw7BDncOGQ3xCo0IlgVSApv/qPyi+ij5ffi4+ID5yPo//If9h/76/vr+4v6D/iX+Cf7t/Wf+YP+LABMCewPWBPQFdgaqBlYGwwX8BP0DKwMzAjABiAD2/xr/Hv5Q/TT8g/oX+Xf3PfVk8+DxBPGQ8X3zP/aR+mD/mwNfCKoMEQ9aEJIQ3Q4FDCAJ0QXeAi0Akf6c/Zn9Bf6f/nz/FADh/8n/KP8F/ib9Kvzv+j36lfkT+T35uPlA+hz7lvw6/hgAjgIfBXkHzwlyC5EMKw3bDOkLdgpqCOYFngOgAd7/qv4s/gX+DP5B/j3+S/4F/o79Df00/Fv7zPqK+or6MftU/D3+bwDsAvEFTghUCuIMTQ7ZDtgPbA8VDtsMnQoICAkGUQP7ACv/Iv3r+yf7yPq++lT7Mfzu/N/9sf4W/6n/AwD6/zcAbABsANUAYQHfAa0CeANUBN0EXgWkBacFmQUxBZcE8gP9AtsB3wCK/2v+ZP0q/Dj7MvoM+Qr4z/aU9ab0AvSY9Dj2Efih+5H/rAPJB+0LwQ5BEIsQuQ85DR8KCQe6A+oA1P59/Sb9lf1E/nj/NAC1APQAgQCm/5/+b/0t/Bz7f/oF+hr65PrB+9z8Vv4DAP4B9gPcBckHggmPCnYLzQuEC6sKggneB7wF2gMXAqQAvv8k//f+JP91/43/0P+7/zn/wv4a/h/9gfwH/OT7Rvwt/Uv+8//7AfYD5gW/B5cJMwtEDCcN9g2bDf4MUgx6CokImQYjBPQB0P/N/cT87vuh+9L7evxe/SH+D/+w/yYAkgCkAJYA0QCnALIASAGHARACuwInA5cDAAQqBF8EfgR0BDgEIATIA/oCZAK1AY8Acf9u/j79A/xK+5j6L/qt+Wv5HvmH+Gj49Pgy+rr7gP1vATwEpAXLCaYM/gv+DAQOYgrUB98GpQPOADQAJP82/gH/Z/+N//QAxwAwANgAxf/z/lX/gP64/bv+6f6j/mgA6gCSAN8BNgK8AWAC0wKVAlwDewNcA8sEegWyBbUGEAeuBnYGCQbZBAQEGQPRAToBIgBj/1z/Nv8I/yT/Uv8d/0T/bv9//+//kgAwAZkBVgJAAwcEHwXxBaoGZAfNByAITggSCNoHlQcoB0EGNAVfBFwDBQL0AD4AWf/e/tD+nP6//iv/sP9hAP8AgAH0AYoCjgKOAvYC+gK7ArsChwL7AbUBgAH7AOYA9ABJAEkAiAAmAGUAwABMAAYAMAA9/13+E/4N/cH7C/vN+Yv4ffiH+Aj6JvwX/hcCtQVSB8MKuAwzDBAMygpyB6EEAgL+/vH8HPyX+178F/5S/98AnwIgA7ADsANWApkBkgCR/qr9G/1b/IX8GP3i/XL+lP/YAPsBIAMqBBUFDQYiBjoGaAbqBVAFAAXWA+wCRAKHAUEBaAF5AcMBZwKYAksCYALRAe0APgAT//T9Xv3n/MD8ff06/jb/4wBEAl8DkwReBccFBgb0BacFhAUfBd0E8gSoBOAEHwXyBPUEfgTPAzkDdQJyAYsAtP/b/ln+7f2n/bX98P1W/uz+kf9QAHIBdQJAAzgEugQDBT4F3QRGBIIDgAKSAWEAlP8r/9T+Af9c/5T/JgCPAJ0AqwApAFn/nP6E/S38PPt8+mf5L/ks+dH4WflL+vL6W/y//pkAogIJBrgHogjtCsAKtgkZCfQGHAQQAqL/U/2d/Mv7r/sU/e39sf5lACIBCQF5AeMAS/+x/n39Kvz8+7r7/PsG/Qn+Tv+gANgB0ALTAxwEWwSTBHAE8gPoA5sDEgMuA+UCXQJSAsoBTwFdAfsApAC8AJYAMAAfAND/Uv8F/3X+8P19/Rj9Ef07/eL9tP7Q/zcBgwLIA/kEtQVBBkgG8QVaBYkEsAMPA0sCvwGjAVYBOgE3AfQAqwBzAAoAfP8F/63+Wf5d/oP+rf5E/8L/NwC8ACIBeQHmARMCOgJPAl0CkQKRAo4CdQJIAu0BfQHYAB8Adf/J/j3+0f2S/WH9jv2u/cr9/v0F/vD9vP0+/dX8Sfys+0r76/qN+n/6lPrT+l/7Efwb/ab+PgDDAbcDrgUzBnkH2gfYBg0GkwQ2AhEAPf4t/DH7g/ov+tb65PuM/NH9zf4I/3//bv+V/kj+2/31/BH9G/0p/SX++v7Q/+oAwwFBAv0CCwPvAuUCogLpAaABMAGIADcA8/+K/1L/Uv8o/1z/bv98/7v/BgDF/9P/2v9V/+z+v/49/tj9zf2x/QX+g/4y/97/xwCgAToCuwIPAyAD1wKAAgkCfQH/ALUAiACIAKQAAgE6AWEBeQFWAfgAbADF//r+Wf7G/W/9Rf1h/af9KP7C/m7/GAC5AFYB1AEsAmAChwJ8AmQCPQLGAVoBtQD6/0D/n/73/WH9Lf3q/NX8FP1T/Y79Av4l/jb+S/73/bX9gP3//Lb8jPxJ/O772fuv+2b7WPs1+/n6Dvtb+577hfzG/dT+UAAFApwCUQMHBEcDpgLKARsAiv6O/T/8d/uJ+1v75/vg/En95v2H/oD+g/6c/uL9mf2O/fj8GP2L/bX9a/45/6b/DQBoAIsAiACEAEIA+v/J/3//QP9A/0T/RP+K/3z/ov/M/8L/FAAtAEkAUABhAEUAFADs/6b/RP/+/pj+Ov4Q/v79Av5L/rj+K/+p/xEAiwC1AMcA8QDDAIsAaAA3APr/AwA7AFoAnQDqAOoAFwH7AKsAegAKAIr/Pf/J/nz+kf6R/qr+Bf82/27/1/8RAEIAjwC1AM4A6gDYANwAtQCBADAA0/9u//r+jv4s/gX+zf2x/eb9/v33/T3+S/5B/jb+E/7D/Zn9a/0m/fz80vyr/Lb8gfxJ/Bz81vt++0P7B/vP+s/63fry+pr7W/wU/ff9Of+0/1cAOgECAQIB3AAAACj/iv6g/cT8pPwY/BX8d/yW/AP9nP3m/VL+u/60/rj+0P5r/mD+bv4l/kv+jv58/rH+Bf8B/0D/df9L/2r/Uv85/0D/L/9V/4r/ov/J/woAFAA3AIsAbABlAG8ALQANAOj/t/+m/43/Pf82/xb/1/73/uX+2/4o/y//Of+R/63/0/8pACIACgANAL7/m/+b/2P/bv+7/7v/AACLAMMAHgFyAWQBVgElAZkAOwDs/2r/Nv8h//f+Fv9j/4b/7/9CAHMAxwDOAMAAxwCgAGUANwDh/6L/bv8T/+z+wv6x/qb+qv64/r/+zf7U/uX+0P7C/qr+ZP4l/u39uP2E/WT9Pv0m/Rv9/Pzu/Of8pPx+/E38A/y9+4X7WPsZ+w77BPv2+k37vfst/Mv8tf1E/tD+vv/z/+z/NADJ/1n//v5E/s39nP0U/fj8Sf1J/aP9SP55/sn+Wf85/y//Uv/X/qr+tP5I/iX+T/42/nz+4v4a/3H/zP/z/xEASQApACYALQAbAN7/8//z//3/WgBhAKQA9ADfAAYBJQEQAdEAvABoACIA4f+0/43/fP98/3X/jf+b/6b/0//J/8X/5f/a/7v/0//C/9D/7//z/woAPgBJAHMAqwDDAOMA/wD7AOoA5gDAAJIAgQA+ABsA9v/X/8L/u/++/+X/9v8NADAAUABaAFcASQApAOz/t/+U/2r/R/9V/07/Tv9u/3X/iv+G/2f/S/8W/83+iv5P/hP+8P3m/c399/37/ff9DP4M/vf93/2//YT9U/0m/fH8x/xz/FD8QvwR/Pz7+fvr++v7GPwx/FD8j/zZ/Cb9ZP2V/e39Pf5S/pz+yf7e/gX/Af8a/wj/K/8y/yH/KP8W/y//JP8y/zn/Of8y/yT/E/8h/yv/L/9H/0T/df9//7D/3v/9/xgAHwA0AB8AKQA3AB8ALQAiADcAUwBsAKsA0QAXATABVgGHAZUBmQGZAXIBQQEeAc4AlgBoACkABgDz/+j/1//6//r/AwAfABsAEQAGAPP/4f/l/9f/yf8GAA0AIgBsAIEAoADOANwA6gAGAfQA3ADmALIAjwCEAEkAMAAfAOj/0P++/5//kf+R/3X/cf+K/3//cf+K/3X/cf9x/1L/R/82/yH/D/8F//f++v4I/wH/Bf8T/wX/Bf/p/sn+n/5n/kj+E/77/eb92P3N/d/92/2//b/9mf1v/UX9Df3g/Mv8qPyv/MD80vzu/CL9Rf1F/Wv9cv1r/Y79jv2Z/dj99/0Q/mD+pv7N/j3/cf+N/7T/2v/F/9P/5f/C/7D/rf+G/4b/lP+b/7T/2v/v/wYANABTAGgAtQCnAJIAtQCPAH0AmQB2AH0ApACgAMAAEAEsAUgBpwGjAaoB2AGqAbEBrgFvAWgBYQFIAWEBjgGEAaMBwwG4AbUBuAFPAR4B7QB6AD4AIgDl/97/7P/s//r/HwA0AFAAXgBMAD4ANwAbAA0ABgD2//3/AAAAAAoAGwAfACIADQAKAO//2v/C/5H/cf9j/0f/Pf8y/zb/QP85/zn/S/9H/0T/RP89/zb/Mv8k/yv/JP8W/wX/8/7U/r/+qv6K/oD+g/6D/of+jv6f/rT+tP7G/s3+u/6//q3+kf58/l3+Pf4e/hD+Bf4h/jr+Wf6O/rj+zf7+/g//Fv8h//P+uP6c/mv+bv6O/rH+8P5S/6n/FAB9ALIA3ADcAJ0AbwBCABEA8//z/+X/BgBQAI8A6gAzAWQBhwGOAXkBbwFyAXYBZAFkAXIBkgG4AdgB5gH0AfAB1AG4AaMBlQGOAYsBiwGSAaABqgGqAacBiwF9AW8BWgFPAUUBRQFoAXYBlQGnAaABnAGOAVoBHgHOAIQATAAtABEADQAbACkATABQAEwAUAA7ABEA5f+t/4b/av9n/2D/eP+Y/8L/9v8DAAoAFADs/8X/lP9Z/zb/If8T/yH/K/89/2f/fP+R/5T/jf+G/3j/YP9S/0f/Tv9L/1z/bv98/4b/iv+K/3j/Wf9E/yT/K/8r/yT/QP9j/3//t//T/97/+v/2/+j/1//T/7v/tP+3/7f/yf/l/+z/GwAbABsAJgAUAAMAAAD6/+z/8//6//3/IgBCAGUAnQCkANgA+wACAR4BNwEbASwBJQEQASIBJQEiATABQQFTAXYBmQGqAdEB1AHpAd8B2AHUAbEBoAGVAX0BbwF5AYsBkgG4Ad8B7QEFAgUC7QHiAbEBjgFyAUEBLAElASIBPgFPAUgBaAFyAV0BYQFBAR4BCQHqAMoAvACrAJ0AlgCEAG8AbABaAFcATAAwAD4AJgAYABEA/f/h/8z/tP+f/3//bv91/3X/jf+3/9f/8/8iADcANAAtABgA4f/M/5v/YP9V/0T/RP9j/27/jf+0/8z/3v/a/9f/wv+7/6b/n/+i/5j/mP++/8z/6P8bAB8AMABFADcAKQAfAAYAAwAAAPr/+v/6/xgAOwBMAF4AaABsAHoAbAB6AHMAhABvAIgAiACSAJ0AoACZAJYAiACBAHoAfQCBAHYAhACWALUAzgDmAPQA+AD/AP8ACQEXASIBNwFMAVMBYQF5AX0BgAFvAVoBPgEbAf8A/wD0APEA6gAGARcBKQE6AUUBSAEwARsBFwECAfgAAgHtAO0A8QD7APQA+ADtANwAuQCkAIQAcwBoAF4AUwBMADsASQBeAFMAWgBFADAAHwAUAAMA\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 14
}
]
},
{
"cell_type": "code",
"source": [
"rate,speech = read(Main_Wav_Data['WAV'][10])\n",
"print(Main_Wav_Data['EMOTION'][10])\n",
"print(speech.shape)\n",
"print(speech.dtype)\n",
"print(rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "rcJ7lZdAtvdP",
"outputId": "ffd21f00-19a9-43ff-c640-379c3fa8060c"
},
"execution_count": 15,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"OAF_angry\n",
"(36848,)\n",
"int16\n",
"24414\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"rate, speech = read(Main_Wav_Data['WAV'][100])\n",
"print(Main_Wav_Data['EMOTION'][100])\n",
"\n",
"Audio(speech, rate=rate, autoplay=False)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "Wu0zvKhotaHo",
"outputId": "8a5fff11-3393-4174-9086-32d0025b1783"
},
"execution_count": 16,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"OAF_neutral\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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+WL5ffli+X35Yvli+W/5mPlv+WL5R/lU+W/5mPmL+VT5OflU+WL5b/k5+Uf5VPlv+W/5i/mL+X35VPlU+W/5Yvl9+WL5i/lU+VT5VPlv+Yv5ffl9+VT5Yvlv+W/5VPli+W/5b/li+W/5mPmz+ab5mPlv+W/5YvmL+ab5fflH+WL5VPl9+X35ffmY+Yv5ffl9+Yv5ffmm+ab5mPli+X35i/mz+X35VPlU+Tn5ffmY+Yv5VPlU+VT5ffmY+Zj5i/lU+Tn5Yvl9+bP5b/lv+Yv5mPmY+Zj5mPmL+Yv5i/mL+Zj5i/mz+ab5YvlH+W/5wfmY+bP5Yvli+bP5mPnB+Zj5YvmL+W/5wfmL+Zj5YvlU+X35wfnO+ab5mPl9+ab5s/np+c75wflv+Zj5s/mz+dz5pvmY+cH5pvmz+bP5zvnB+dz5Evr3+en5zvnB+ff5IPoS+un5s/nO+RL6O/o7+i36EvoS+hL6IPot+tz5wfmz+SD6Y/px+gX6zvnc+SD6Y/pW+i36IPoS+vf5Vvo7+hL69/nO+Tv6p/q1+jv69/nB+Tv6tfrr+nH69/kF+hL6Vvp/+n/6Y/r3+S36Vvp/+pr6cfp/+sL6f/pW+jv6Lfo7+mP6cfpW+kj6Y/pW+lb6cfq1+tD6jPpj+nH6p/rd+jz7tfot+hL6Lfpx+uv6PPvd+lb6SPqn+iH7Svv5+n/6Lfo7+nH60Pov+936f/pj+nH63foU+wb7wvq1+t36tfqn+tD63frr+t36tfrQ+vn6IfsU+wb7IfsU+yH7PPvd+nH60Pov+4D7c/sv+7X6wvpX+8T7xPtK+6f6mvoh+2X7gPtK+xT70PoG+6n7+vvE+xT7+foG+1f77fvt+2X7Svsh+5v7+vu2+477ZfuO+0r7PPvE+9L7qfup+4D7Svtz+6n7xPsI/NL7Zftz+8T7Ffyq/DD8gPtz+5v7CPx0/Ez8m/tl+4D7xPuP/OH8Z/zE+4D7m/s+/Kr8Pvyp+1f7jvs+/NP8qvyO+/n6L/sw/Fv9Tf36+y/76/pl++H8kf3G/I77wvpl+7j8uv1b/T78L/sU+yP8W/26/Wf8V/tl+7b7/PzH/fz83/ub+7b7j/yD/br9xvyA+4D7Z/ys/Z79xvzt+9/7nfwX/YP97vzu/Aj8CPy4/DL9Cf0J/e37+vvG/OH8nv3T/Aj8Z/xZ/ED9QP1o/Rf9WfyC/O78Cf2D/br9nfzT/An9dv1B/tX90/z8/Hb9x/13/gv+QP0k/ZH9QP2e/U/+C/5b/dP8Cf26/YX+T/6e/eH8F/0m/mr+8P00/sf9kf3G/IP9av7k/mr+Tf12/Rj+Jv7w/az9x/0L/v394v39/ZL+NP7H/U394v2S/pL+XP7V/Wj9Qf6S/nf+d/5P/hj+XP53/mr+oP40/mr+yf41/67+C/66/Vz+UP/x/v39uv0k/aD+yv///q7+/f2e/Sb+5P7//l7/8f4m/oX+NP53/jX/Xv+7/uT+hf6u/vH+ov+u/ib+5P6i/wz/XP5B/tb+r//l/9b+rv7//uT+Nf+9/wAA2P/J/hj+NP7J/mwAUQCv/67+4v3J/pT/NgBsAIb/kv6g/nn/yv+i/wAA5f9r/7v+8f7z/2wANgB5/5L+Nf95/17/DQAAAFEA5f/W/rv+lP+i//P/lQANADX/DP+G/1EAegBsAAAAXv/Y/70A2P/K/14AKABr/4b/hv82ANgAbADK/ygAXv///tj/DwHmAIcA5f+F/lD/NgB6ABsAegBD/7v+lP9eABwBHAFDAGv/vf+VALAANgABAYcAlP9DANgAegDY/2ABhwBQ/1D/XgCxAegBKACG/8r/GwC9APUBpAHK/yj/Gv+wABACiQGwAMn+yf69/xwB6AFSAeX/AAAbANb+DQAPAWABvQBe/ygADwFRADYAlP82ALAAzAGHAMsAKACU/3n/lQArAhACegCv/8r/NwGJAbAAbgEQAtgAsABuASgANgCWAQ8BHAE3AVIB2ADY/4cARQFFASoBvwHMAQAAAACHAGwARgLoATcBvwHY/1D/hwDOAlQCbgFDAAAAhwBgAfUBKADYAKQBywAeAuYAGwDaAQMCvQB7AR4CUgHYAGwAHAGzAkYCUgE3AXoAvf/MAekCKwIbAAEB2AAqAWICKgH0ACoBbABUAoAE5gDk/noAKABGAoAE3AIM/6L/bACxARACsQHAAr0AsAAqAWABRQEPAegBcQOYAlEA8//YAAEBRgJiAmIC2gEPAeX/2gESAwEBDwE5AmABDwFUAgMCvQC9AHoAsACKAswB9ABvAnsByv8DAhwBEAIcAQMCfgMDAjT+sQEeApUABAMcAUMASANiAkUBUQDmABwBpwMtA7AAvwErAkMARQF7AW8CVgNjAwEB8f7YAB4C9wIfAzkCd/7K/2ICYgKlArAADQCJAfUBbgEeArEBRgL0AF4AbAClAgMCBAP0APQAhwArAm4BKgGzAokBVAI3AX0CpAF6AIkBYgJjA9wChwAPAcACOQKkAaQBRgIPAWICUgHaAXoA2gHYACsC9wLAAgMCyv+i/4kB9wIfAzkCHAHMAQ0AXgCJAdoBOQJxA8AChwBRAOX/NwGYAn4DQwDk/pUAjQQBAXoAlQAoANgAiQH3AjkCvQBQ/wz/HgIrAt0D2gG9AJUAlP8eAlQCegBIA34DlP+9AGwAbgH4A30CNgA0/mABBAPdA0YCKABb/Xn/VgNlBIAE2ADH/UP/DQDmAKcDwgMrAsr/5P7W/hACjQRiAsr/u/7MAVQCzAGVAF7/2gEQAooCHAGG/2v/swKKAkUB8f6kAQ8B9QHLAFYDDQBRAGABsQErAn4DNwGVADYAywA6A9oBbgG/Af/+r/8NADwEtAMPAeT+GwCHAEUBwgNWAwEBu/7l/2wAYgITBDkC/f1D/5YB6AEbAMIDDQCG/yj/lQCnAwYElP+G/4b/lQArAjoDYwPz/2wA8/9FAWwAgATMAcr/2ACzAmv/pwOpBHb9Jv4fAx4CwgOYAssAu/5b/Q8BIQRNBr0AQ//w/cwBNf+lAtADKgEo/17/egCJAcAC2P9iAssAHAE1/28CsABgAR8DDQA3AQEBNgC/AcACiQENABwB6AFr/3sBSgQDApH91v7k/rQDnQWkARr/Cf16AOkCcgQ2AFEA8f4o/78BSwX3ApH9QP0BAQ8B3AKnAygAav42AMACvwFDAKUCewGWAegBDQC/AWABHAHpAs4CRQEPAfP/vwHrAzYAvQA0/koEpQKVAFD/GwD1AR8DYAFSAdb+//4uBKcD2gF2/VIBKgG/AQMC2gHpAg8Bkv6wAGICKwIAABMEbwKg/mj96QK2BF7/lQBSARACsADJ/tgAbwKdBQAAXP7H/cACqQSlAjYAUQBQ/73/9wK0A5sE2AD9/eL93QMGBNADvf/u/OgBlgHdAx8DsQE2AJT/vQDcAm8CEwQ0/sr/AAB+AygA0wW7/uT+NwFiAu78TQZWAxf98P2NBBsA9wIkBlv9nv1SATcBqQSPBZ38xPvfBAQDVAIeAusDI/xB/rgF3QNc/lcEGP4BAfcCyv8AAGUE9wKq/PQAHgKi/+gB0ANgAQz/Jv5yBN0DUgHl/3sByv9c/lYDawjYAHH6GP7iBrYEogBSATcBI/w6A/gDuAWlAp79NP5RAIAEngYGBD78TPyi/3IEnQXrA6L/aP0o/xME6wPFBX0Ctvs8+14ANgkaCL0A3/sk/Z79/Qa2BIkBVwRn/ID7wALTBR4CjQRD/1b6pAEyBkgDkv69AL8B8//3AvUBav5SAZYBzgIfA/P/0/wDAt0D6AEEAwz/hwAAAF8J/f30ADYAKACJAWUEBAOq/PUB3QO6/U0GDwHi/SgA3wQQAowDJP1b/Z0FPgUrAo/8hf7aAQYEcQM6A0z8F/0GBBMEswKVAGL5EALRBNoBlgEbAJUApAFGAjcBvf8jBXf+AADcAooCg/2v/9EElP8QAmMD9wIG+9wCHgLAAmYFYgLc+cb8DglxA2YF4v3V/Wr+pwOSB6//Z/xXBFIBUP9xA+sDjvsDAqQBbwKPBfUBrP0w/I0EvQBNBtMFGv9N/a//6AG9AHUGxQWs/SH7Nf/7BfEHXgD8/Az/ywBiAo8F+gR3/sf9Cf1UAkcLmALH/Sj/hwBIA0sFigIAANgAXgDpAugBav7fBPoEYAF2/V7/mAKVAKAHhwCxARf9vf/1AX0C4AWWAf/+aP1RAGYFjANIA5L+XgAtA+gBwgMeAkUBGP5B/loG+gTpAqz9C/4DAk0GYgKpBOkCaP3Q+uAFiAmzAuX/oP5A/YoCHwOwCTwEBfoL/lD/xAQVBRcGegCs/VT5bgG0C2ILXgAP+DL9RAnvBowDcQN3/hX8Xv++CVYDov8L/oD7YAFIA/0GnQWP/OX//f1+A60HxQVq/l7/Cf03AZsEWgbw/db+Mv3RBGUEEAI+BWwAdPyv/4YILgRIA+gBCPxgAWkHtAMBAVz+RgKnA7YEDQB9ApkDyv8qAfcCgARjA4wDpwMv+9AD0AMYB7QDAABz+1IBhQf6BGABov/QA6IA9AD3AlULbAA1/0UBAwJUAtkJnQX8/Ez8ZQQ3AdMF5wl5/5f4fgO+CT8G+AMo/xf9RQEqCtQGVwSU/1v9vwHlCCMF0AMPAXsBYAHMAXQFKwIHBYAEF/2RBg8BigLdA/sFnQWR/QAAZgUMCNYH5gB6ABr/xASGCP0Gav5eADoDwgPTBe8GbwLmAIkBigK+CfYKu/5A/VcEvgkTBFkFKgFKBFIBWQVXBOMHPARD/x8DuwcLB9wCJAY1/xsAfgNKDaUC/weu/iT9cQMXD6kEswJsANgAZQSTEOsDqvx0/LAJrwhfCbsHg/3i/RACWQ4ACWgGg/0Y/jkCwwxxDAkGGv/d+p4GLw0DC24B3AKv/7AACA7zCOAFBAPW/hr/Iw7PC6oF1v6P/PMIcAudBXcHPgXE+zIG/A50BWMD+gRWA+UImwTiBiQG5f8zB80K+wW6/X0C+w13B9EE2gHEBL8BLAsuDPcCqQRuARcGDAhwCzMHtgTMASgAJAawEaoFLQOHAOIGOApGCrsH1v74Aw8K8QfiBmILAwLl/0sFRAkACXALQQdq/mUEqAy8CJEGRgr0AHEDlQlHC9EENQj4A7QDZgXOEx4CzgK4BQYEygg9DXoJzAHHBoUHQQfwD80K8f4jBVIJ0AzZCT4FBAOqBUYK4gaBDWkHUgETBEcLhgjjB+8GlAi+CZ0FAAlZBVMKuQbzCNsKaAaSB5cKGghM/CsTgQ0hBF4AKBF0BQsHVwSLCyoKNQiwCXQFYQoPCscG5wnACmgG8whnDksFzAnnCZUJ2gFrCCgRKgoLB80KPAQjBV4ROwwkBk0GAgr/B+4Fgg6oDJkDAAk7DIEFpApkDHUGIg2TEBAChghAD20J8QdtCTsMxQVkDDoUaAZdCPMIhghVC/IQGgjiBq8IsAmmC7sHURFmBXQFvgkgDLAJVQv3C8oI6wxfCXMNKQmgB2YFJQ81ETYJCQa7BywLMg8OCeUIzQrvBosLkA5HC2gGNgk/BmkPAAnrDBIMwgOGCL8S9gq8CJcKeQgiDS0UnQVdCGsIkQawEWwRJgfqC7cN3AKyClUU0w6jCe8G7gXqC7QUZQ30CfgD0AMXDy0UCA7MCbYEDwFAD5wNOhT8DjcBKgFiC8IUHhPTDnn/OQLJEEEQ1xBKDccGNf8bCToUHhOoDP0G7ARTChsJuRexEhUF2P+tB8cPVRRcB/4PXAcmB4MGEBNqEJgLFw9XBAQD+QzjGCkJbgGoDIoTGghGAjAWIAyjCV8JKgrvBkYTWw8LBwYNAgrWB6gMNxIDC3kIJwj8DgESDgl1BhYOQgj5DOEOUwpSCVYMsgoOCWUNBg33C9MO6guVCW4KlQncCz0NjBQ1CMwBmAt7EjURRAlCCCcIxA3tDcAKohGLC3b9nA3qFDURmAIwBcMMTxDwD6AHlBFfCRj+zBIHFnUGVwSwCYcR3As5E7wIswLfBPoV9RLTDusDRQH3C8cXOAqLC0EHcQOTEDURuxA1CLv+rhBHCw0RKQnMCcsRgwa/AZYShhlgAfcCChhDEZ0F7AQeCxkZUAjiBtwCrA9REfsNuwdWDLYE7gXdFMYOVgzZCa0HGAecDd8N5BDrDPcCBgTYEXYPNQgXD4QPoAePBaoFug/9F9AM1v5XBCYQzQotFOcJuAUACXkIdQ6mC10QGgi1DK0HPARGExMVhghD/wwIORMXBkwOlBHLAJsEGRB4EPMIfQs+BcMMmgzoCmgGtw24DnQFawgsC9gR9goLB40Eqw6pDeMP/wf6BLIKXQgjDiAM8whZBYUQgQ2PBaQKJQ+5BtoBBxaIEhf9vwGuEFUU7wZ0/NwL4Q7JEDL9bgpJFb4JevfBCxkQMQ60Ax0KXwlBB9kJGRDlCMUFxQURCxATxQVOB8ELnQVWA8oI5xJyFSEEKPdSCR8UNRGtB2wAjwVDEa7+bRKkCtQG+AN7AYwUYgurDkMA2P82CYMXAAmpBIEFLgS8CKcUmAu4BYoCIQTbCi8NmRQ5AtP8r/9hEy0UhRD99HcHlQC7EJQRLRRF+BT72woSFIkK6wx6AP0Gnv1QCJAXzhM09t0DVgyJCgQDWQ7BC4D7kgdkDIsLHgL0CYoCQgiRD5QIdAV1Bib+8QcGFVkO/Pzk/kwOBQzACloGqgUrAuAFSQxjFG0JRfg1/10QIg28CBQNMPwX/YUHHhPnEm4B0vNcB5wWsgrG/KwG5wkm/h4LqQ0CCnn/Bfo9DY0VfApWA0z8xAT9BoAVrwgqAS/78wh1DmYFGhGVAHcHhf4dCv8HwArjDxT75P7zCL4JGAcCCs0K/Pzw/WsI5xKYAosLlQBRAHEDzwuhCIUHEQtP/hIDngaSB6kExg4OCc4C5vcACcwSjg0QAqr8bAD6BIgJxw9QCM4CCf3RBBUFRRsa/zL90QRgAdAMIw7pAsf9Nf99Ah0K8hmbBBntdwfwD90DRAmNBFz+/f1JFTUI1f2ZAzMHGwBSCewVUPa9/0EQsQF5CPoEQghQ/7EBIg1ECawGdv1N/YsLRwvuBVcE8/9LBeX/Cwd5CDMH1geM+vcCHQpgEpYBjvtlBOUITgeqBQsHegABAfH+GAfyEBACKwL1+EkMtw0bAJr6cAsKD9r4uAVtCan7yAd8CnIEqftECckQkf1s9zsMLAv9/QAAtxYX/br9GghkDB4CIwVK+3wKzQq6/esDBQzoAdT06wzMCXUOGP4PATn5YQoOCdkJ0/x6CZf4d/7YETgbv++r9GEKUhJNBn4D6AEo97QD/g9uCigArP1D/14AARLKCAb7cQPHBgn9vAg+DowD7vzEBK0HbwLdA6wGfgPDDH0C8OySB80bMQ7b8IoCyAeGCLwIqAyO+2ABewGMA9INLAt49hMEfAq0A5UASg1sAPQAxASsBowDRAncAjz7RgoACQMCtAPw/RsJ4AVc/n8MZAzd8Yb/whS9EdT0rfUWDjQQtvtyBAMLXv+d/PYKiAknCL3/+fpVCzQQrP2V90oNJAbLAFAIUgFhCo77SwWeBlISHvmN8nwT2wpeAJUJawgY/pr60AwDC7wIzgJl+ysCCxAVBWf8OQLPCyj/gQX6BGgGUAjLAHcH2gHOAgkGoAeRBgYEQwDV/TIG2AgACYP9jAMa/zYJbACeBscGDwEa/zIPtANuAYAEwAIGBM8LUwoSA4n4YgKQDqQK+vsaCF8JNf+F/g4J6gtSCZf4g/0cEsQEpwNCCI/89wIYB2UE+gQACQz/BAP9Bh4L9QFiAocATgebBO8GAwIbAFQC+w19ArMCuwe0A1kFmQMACXIEbPc9DbIK+gQNAOAFuQZQ/34DYQpcB4P93/uMDKMJmgwACRfsjAP+D10QvPagBwMLvQDt+3MNUAiqBST0BwV4EAkGM/XsBEccbPfj9c4Tdg93/h4C+wUoAL736wz/EH8MI+vu/LAR8A/5+vP/nw+9ABL6ZQ3sFRn26/pDEZoMd/7x/lkW/Qbo+GP6dQ47DBr/fwzk/qT40AMhFXoJWvQ8BOoLCQY2AFcEmAsSAxACaAY/BicIUP8TBIwDAgoVBbAAvwEKD+MHhPWXCsMMxvzxB1AI9goA9x8D1Q8PAQwI4wcl9agMyRBB/r3/iQp6CdT0GggWF8QEKvhFAU4H+ANSEpsEPAS69RACAhOdBZL+JgfEDSoBI/wqCvMIVAIXBh4CbgoJ9AsQURHV/U39OQJaBhsJYgu9/0f5jQT3AqgVvglG8LYEFA1HC/r7zAEDCxUFtAPG/JcKzQpq/kUB0wV8CpUAC/6LCz4Fav4tA/oEiwtcB/P/oP7vBnUOUQDUBswJUgnC+kUBqgW5BogS0QRy8r3/rA8DC5YBSg0k/TYAywAHFvQAZfvDDH0CIQTAApEGzwvHBtAD8f7UBnf+3wQAGsr/SfJZDiMOyf7l/4gJ3PmMFNIN8vYh8rEStxba+KIAkQYSA2j9/xBmBZEG+wVyBPcC+gRFAfIQAgqf7E0GuxCbBNYHuAVl++oLWQWYAmMDzAloBkP/kQ8qAeH8MweeBiwL8whaBsf9RQHcC0YCBQwXBuL9iQHnEnn/wAKODQ8KEPBNBn4UrA8rAgn9jvvW/rMcfArYAEXvhQdDEUcLgPsDAq8I9gq9/+IGpwPRBBsJhwBU+d8NoBAsC1jzQwAcEjAFhQfHBpYBJP3HD9AMGPUGBHoJKAAPCl0IAgrdA2ABPgXQDCQGwAKYAjsMoQhA/b3/WA1lDV4AfQJxDEz80ANREYD7HwOhCMIDvgmkAXALQwB8CtD6ogByFYgS9vC9/1kflP+j79oS6wxOBzcBMv2bBDIPtAsbAM8LmvpGAiAMsxMf8Z0OdAW0A2P6aRhI+hMEfBM6A875EgyRBob/VQu0C3oAmAsBARIMGP69AJwN4Q6vCGMDoP7u8/ccxRat9SD6+gQNEcf9NQgjDloGfvEnCO4W9wIOCSMFTgcN9zURjBTMAbX6CA5wC2r+XgDwD6oFbgH3AhEL0AMJBk0PEfk/9NAMpx3OAlXx7w6NFdMFnfyYC9YHVgOMA0YCKQlTCuwEdAX1AfP/BBSMA1D/iQp5CJT/YgKIEsgHexLu89n3OAq0FCUPNQgf8cQEYRPRBNQG+wWPBT8GBAMV/PIQngZpB1kFvwFUAmEKXRCi/7IKhQeUCK72qAyUEeUIRgIt+s4Ctw1SCc4TgAS28jkCmBybBEz81Q9NBun5zQquEK8I5P7ZCRL6LgRFG0IIG/fu/CUYhQeP/MYOTQ9X+9wCAwIgDO8GwQsGBCYHO/r/EFULfQs8+y/7kQ8gDLsQegC7/qAHBgRVC/cCMxj7BYzpgQ1dEDwESg1e/17/ov8dG+cJq/RrCJEPygiN8joU1gd8CmILT/7S+3H67hYAGh8DRe+FB0YT5gBe/wIb2P9b/WsIWw9+A0oEOguU/2D4xxfVD3P7QwBLFvoE9/kCCm0JVgPk/n8MXAd9CyYHwfnZCRsJeBDEBMb8X/e5FxQNffnEDZgLh/cQAhYXHxQM9h4CmAvxB/r7/A7kEDz7QP3mEeL9vgmFB5oMGwCwAOgK0QSLC1ULAfjeDMwBXwk7DLMCxvwGDWwR1v55/4EFwwzEDeT+OQLqFD8GqftSAaUTrv4sC9gIhf5uCtAD8P3zEVcEjwWFB2kHh/d8E/0GNf+mC1wH4AWU/5UJ3wSZAwAA8A9BB78B5QjlCF8JEQte/+4FaAavCAkGlQCIElcEJv7Y/ysTcgQo/+0N6wNgAdoBHwPXEEEQ4fzs8voex/1o/dgRoAf5+lD/1AY9DYgSs/lxA98EjAwo/40EuA4FDJnx4AVpD7sQK/BmBcoITgeDBg0AeBAtA7EBGwAqEob/ZQRuCoAEMgb1AYkKohEz9c34sxOWEuX/qQT//ogJkQYTBIEFhA9SAWUEgQWDBrQDQQdB/pH9aBfCA8Lx3gweE0T34v0yBroPvAgcAUMAAAkwBXkIkv5AD5QIrP1KBMcGaAZjA8gH3AJjA5sE8f56CW0JQf4tAxIMav6cDUYKLQMq+DcBwgPuFrkGIfuJ+LQL6wNtCS8NmAsl7IUHxw8JBs4CYAHV/UEQvQDi/d4MMgaABFYD8varDvgUf/qV97YEqQ11Bm/5ZgUOCRIMrAYq+OP1kBcqEnLymvqCDuMH7fvMATsMNQij96YLnfyoDGP65QhNBlQCUQDvF1YDFOrQDCobxvx/+t36cw1MDqIA3PkoANMW8f4BAXf+kQYbCQMC6wNc9e8G1AaED7D3bAAjBYENC/5b/S0DDhJo/dj/TPwXBgAA8//zEZH92fc+BWILav4lD+H8D/hpD+T+UP9pByMOUPY1/xAClP/6BGILPwaR/cwJEvqyCmgG7vxsAGUEbQnW/rD32AiaDKIAVwQa/y4E4gbr+q7+uxCF/hL6tgT1AbUMuPy7/tMFI/yeBtMFRfheAAgOlQCO+9n3UAhmFo8FlOUtA20S5gABAYUHpvlM/BUFUAi6/XALFfxi+TgKQ/8uBCkJp/rm9xELJgc2AG/55f91DhH5XgAo/1cEoAfk/vQAzAFP/rb7zAk/Bq0HHfhX+6z9GRBY85sEtAvaATDzqQRvAs4COgNlBOX/7vOICfYKwAL098r/+APT/McG6AErAjL9zvm9/60Hav7vDnwKi+iq87QU1geC/LTxOgO5Bo0E3Pnt+zIGiQFs96QBXwkJ/Vb6qft1BlD/Xv+KAtADwvqRBnoA3fHmAAESg/15/yMF5fb1+PQAXAdDAC36KgrG/NX9j/wHBUH+QgjX5RIDmgzcArX6RQH68kgD6wwh+2f8Pg4q+O3qYRPmEezyX+b2E0UB3fri7NcQAAAkBnv4KP8h+6wGNwGX+JkDGwBi+ZEG/f0g+g8KlQA37xMEBAMw/CMFzvn48TYJEQu/+J791f1R94AE2gEfAz78/vVRAOAF7vy4/NADTPye/TX/PgXf+/P/3Pmb+z8Gu/4bADL9C/689rEBNwHRBH/6ogBg+Gv20AxQCDP1qPJ6ACYQTgcO7132zAGdBUL2GP7zCMn+x/3S81LvmAue/Xn/iAn1+FfyQggEA132GgiD9E399ABoBoP00wVb/Tv6EAIL/p0F3/u9/xn2W/3lCKv0Qf7PC+X/v+cUDaT4L/txA84CkPRD/3IEDfd7AbgFEPB7ASEEYvlcB3IESuHvBlcEV/ttCYv5k/a7/nr3nv3yECj3JP33+V7/QP1uAcXz3QPOAt/7mPn0CR34LPnjB4P9Nf/u/G/5tAvX9iz5UgFRAJL+4/XKCKn79ABc/sf9DPYo/3oANf9tCX/yj/zuBarzvPbLEVIBf/K9ADj4sQHsBIz6wPDCAysC+foq+IYItfoR8fQJqfs7+gkGe/hX+8YOOPgm7aIASAObBDkCrP1A9aH2wwxE9yj/9ACU/7z26PjaATIGJv4v++37nfx5/6UCsAl3/hj1Z/wq+E0GuAX3+csAI/wR+cr/Q/+b+wYE3fEmB7EBTPTYANb+2u8LB3oJ9/mB8+gK+/NT+NYH3ALM79X9Q/+kAZgCvvfFBab5YvliAkP/8P0o/3f1lP8mB1DugAT9Bhn2tgRm88H5vAj6+6f6KP9r/1H3cQPiBnUGdOs+/PP/rQcD+SD6eQjx9Sf28Qcw/P39ewFA/cf9LPn3AlIJ1/Z+Ayj/CfTr+rsQKAAE8YD7yf7d+kkMNwHL96H2NP4J/ScIwvrV/W/52P8J/TAFAwKg/oz6hwCS/vH+Tf2KAtb1egBM/D78x/34A2IC8vb48RwBNgnO+Rf97gU8+7P52gEV/MwBQghu+Dn59wL99MQEWgY8+6r8D/h9+d4MJgfS+6v01v4I/OwErAZN/fr7dv2w92ABYAG0Axn2kv6q/MsAGwAV/JkDtvt9+dwC8wgh+zP1Z/yeBtz5//5SAVD/pvlx+toB2wpR9xr/bgEy/aUCkvVZBUgDL/uL+VwHa/82Ca724/We/VgNn/Xi/XUG4fxR92r+2P/YCBMEd/Ui80D9ownK/wMCUQBk8r3/+AO2+4oCdweT9uj4SgQhBBwBtAPG/PH1fgPi/fcC4gam+Qz20/xwC2j9WfzBC4T13PlXBFcErwiC/MXzTf39BusDf/ov+8QEvwFo/Wbz3wRWDJ38MPOICUP/7vwQAkT3ifjhDiQGV/IU+54G/wdsADD8NvfY/wsQKPfc+WwADP8a/8cGb/B3BxoRmPma+nn/VwTEBDb3TPxCCJ38oP4XBq31Cf36BGj9rv4IDmwAbvh0834DwQuk+GABxg7N+E/+mALG/HED/Qbi/Rj1GwAk/SMFzwvd8YkBpgvD8mwAEBOH94v5ofY299INxQVe/+n5sQFo/ZUJvf+ICW74SPpi+Xr3ohGWAWj9UgEn9ugB/A7j9WwADwGC68AK2AB0/L8BtfpXBGUEyvbqC28TeO0o97EBePYUDT4FjuplBKwGwvqABL4Jhf5iAuDzEAI5AloGa//r+hIDYgL1+HwT5wkW9ED9owmYAr3/HAGjCVLvOvEtFOgBCf2j95L+EAKd/OYAnfw8BDAFYPiYAjL9YAGSB4D78P1SCYP9AwJc/jj4DgnO+dT0hxFe/wn02AAuBHf+DP+kCgb7s/lB/uQQQvbQA3T8R/kd+NMOMPyXCqUC9/lp9Z0OxvTWB7r1YwMcAZAOewHm96QBYgK4/Hf+VwShCHvvafV9+bkGLgysD6r8Yvlc/pYB5gDx/uIGdPyJ+JIHJP20Czn5D/jW/rX6xwYJBvgDhOyA+8MMCPyYC0j6AfjQ+kcL8whM/KD+jvtZ/CsCOgOQF1IBrOMo/8ATmPlpB8XzaAas/Q33exLsBPr7mALu/Jj5RQFfCTT+g/2h9usDug8F+ugBAfiq/GEKm/J5/yoKj/x2/ZL+fflmBUwOaP0NAN/73Pn3ArEBm/sTBKIAnfwo97j8ARKKAljzve4YGAIKaP2wCR75CvWKAnH6bwJwCxcG/uykARr/YgtrCK//evdOB1D/YvluCrQDse8D+VQCsAna+Pf5SANN/afxBg2PBYrwjAzQA1TwKACi/00G2Qmt5OUI3Atl+x751v4h8pEGwgOD/az9PARj+sH5Dwra+G/5Q/9LBYAE1v67/sT7H/FVC/MIBwUfA4vxLQNvAhT7Oguv/0/+DffY/6AHkvWBBRACee4FDMQEvwEHBXP7e+8eC7b71f1mBSb+k/azEw/4yPWvCOv6CfQXD/X4VfGsBj78W/1b/W/5IfvUBiP8AAlu+BPytfqY+e4Fkgc2AIzpSANvAuH81gce+cXzwgP3AjsMNBA/9G3vm/sKD8AKiQpx+qLuYgLT/GMD4gb1+B/xFA0bAK//uwc8+yr4ogDC+rgFIQSH9xT7nv3W9Y77SgTd+hT7Qf7u/H/6ZfsqAdD6cvJGAtYH+foP+K8Is/ln/An9gAQ6A/n6u/7KCID75f/MATL9av76+78BUQC9/wP5KAA5+fr7xASq/Fv9OQISA+Dzyv8w/BMECf3p+cwBFfy/+DUI7vyS/sT70Pqz+VYD+AOL+Yz6vwED+cr2xA0L/gz/EALi/Wf8Z/yg/pUAPAQm/v30g/1gAST9zfjKCDn5HfgkBgn9jPrYACr4aPRWA0P/V/shBHb9l/j4Axv36AGC/M75pAHQ+q7+7wY09mf8VAKO+0YCFwaa+lv9wAKN8jMHF/3p+U4HtvuH9yEELPk/9HIEFfxA/WYFqftj+mABA/keAvH+/Px0/In4l/hLBVb60vsDAh34BAN/+hj+/QZ0/A/40ANT+N360APUBlH3y/cq+LQDNP7f+/r7vvey+BsAVgOs/Qz/MAWM+nIEsQF7AYoCLfoQApL1zvnWB3T8KPeU/1n8QP3vBtX9XgA8+0nyW/3YAJT/UAh69wz27vwU++MH+AP6BDT2FvRsAKD+5gCG/xj+ZgW89tz5qQS7/i4EzvnO+dj/YgKbBML6yf5P/jcBC/6s/QYEuAXC+kj6sQFR96f6DP+wACYHrfXL9zz7LfowBUD1KAAk/ff5BAOb+xb0afWk+BH5m/uWAff5m/L+9Q/4CvXG/P39Y/o2AMj1U/jc+Wn1nv2FBzT2YPgJBjT2gfPN+F/3l/j6+wMCOQL1+M75wfnm9xL6gPv1+GP6tfoBAQj8JPSO+ygAzAFb/eYAWQWY+b3/sAlu+G/50AzIBwYEEAKO++78BgShCFAIfQKq/PMIngbdA9ADEvp7AZ0FTgfvF0YCu/4fAxf9jwWmC1wH2gFI+uYA7ASWARsAMAUeApH9lP/EBJgClP+/+Bv3hv+s/dX9DQCy+Dj4bPdA9Rf90vtC9tX9Muz863/6nvSM+jDz6+kl7CT0Xfa28lTwPepQ5Vzt/+0Z7VvsIOkO5pDrlO506x3w6ujo50HtH/EE8ebu8u1v8C7yMPNI8c/x7/SE9fL2/vUk9Nf2uPyVACgAlQAk/a//yAdNBtMF/Qa2BKYLuA6cDakNtAvQDBIM1Q8cEqkNYRO2FZ0OgQ3aEnUOXhE0EEoNsBHnCQMLKhIgDOcJngbQDJEPSgTlCEEHywDrA+UIKwJ6CakEe/j1AfH+0/zl/wb7hvYA99L7Evqy+GD4QvYG+zL9zvly8kjxe+9c7bPwo/ev7sbr+ekO5n3oeub+5HrmqOGk3ubdHN6F3J3aot3s4arieOVk6WPgmeB04pngDubh61zteuYt6Vbp0upG8CLz7vM29wX6hf69ANb+gvzQ+uT+VwQbCR0KGgieBpQIlQk9Dc8L9wvZCfYKgQ2+Cf8HWgY2AOkCXAfZCXwKvAjEBKUClP8cATAFHgLOAowDLQNWA2MDVAIqAZkDMAXZCZoMOwwzByoBnQX0CRcPexJADwoPqQ12D2oQTA6RD9cQkxCUEUAP4Q6ICYgJoAcoAPoEAwsACTAF+vur9Bn2wfk29xHx5+9Y6irnAOa54x7fE9gm3Arbt9k23XnUzs5ayTfEScdIzxTZfdc+2sjbDNTo1g3dGdzm3S3gg+OG5Qrsqerb53nu7vMj/IMGEgwDC5IH7gW4BXoJFA3tDcwSOhSWEt4VExWIEnsSURH1EtsT9hNbD1AIbwIL/tP8//5iAg8BGP76+zb3P/RY8x/xe++H7vPus/CI78brVum16cntP/S/+BX8yf5b/TL9YAG0A+IGlQmoDMwSExUJFwwZsBpUHF4i0SbPJQUmsSPVIPwf3x6vGf0XOx2/G1MbRBoeE/kMHgvzCLgFDQDQ+qv0UO4i6v3j6+CK32faVdfW0/fORc1Xx6DC7sBUvSW5XLlMuAS1tLUJwY7I5ctk2FDUEM5S1XDXrNt93/vihuWA6rbyl/jK/4AEsgoaEZUaTSDCHfcckBeEGBQeqR5GJBMmhyJ8JM4k6SSPH4wdbhv2E0MRcQxXBOT+lffR8rPwtPHO8A7vL+oA5lTfndrv2ovXntLg0Y/RP9IY0xvVN9XQ2LrbPOGJ547qo+9085fw1vVe/2wA+w3NG7McOCT0K9krnjHKMx820DdqO4c8GTuhO1s6YjZJN200rzN5M2MuZygaIkEYvRHkEGILWgYoAHP7IvOE7FHmvd3s2GHWV9CtyjjF973CtbuxkK90rwux/rApswuxoalTq7KreqpivXbKfc6o2CPastYZ3OLjaOyz8Cr45gCeBnEMoBCRD8MVFB6aJk8y9DSyNZEx/SiTKjQqqifmKw0r7Sf1I4UhEh0fFN8NNgm2BFQC1f108wXp9d5J2KHUx9I11FrScc/azRbJscR3wv/CecPYw9HHKs2az53RANWm15Pc/uQC8OP10vvW/toBxAQqCp4XDiMxKLk5LT88QEBLQ010SodNy01qTClObE3bRsRART2BOGQ3+DbwMQ8sECQ1GZYS8wiHAJ38QPWX8P/tI+vW5K7cHdbOzvzJPMfVwSm7ELQsrGamfaOYo3Wnean6rtiyl7TPtfa0m7YzuZTDONa44lvs3vJJ8kD1T/4hBGUN+BSrFwsh9SM/KAkoWCfxKUUspTXSOII56DUBLOcj4R8gHTYaDRqxEoENeQgoAIz6K/CM6Sbk6+AP3gXYdtKByDXDmr6kvHO/DsSKxUTEPciXxTDIOc4G0KHUMdpl4bPo5+9a9L73F/34AyMOLhX3HNUgGiJ+JYsloSo7LuIxCDnpPjxAEkiQSpRE/0OAQFI9NDvgODUz9SwHJ+EfiRutGOwVYROHES8NxwaU/5X3i/HT64nnieek5wDmhOSB4rHeyNtq3ILaYtfz1ErQ7ciHwy+/KrwUv0PDLMahy3HP8MrZzEfOjtBg3jXui/HN+Dz7P/Qb9579Mv1lBDoLrhAVFlAZ8hnFFoEWeBlsGjQhHSRlHnwbUhIuDH8MOgv3CwUMlQk+BUUBV/v68ljqKucz5FfhaeTr4EDbB9lB0wnShtQH2ZDa1duu3DTcvNyz3xXi8eRM69rvifii/xwBLgSBBeIGcQzMEjEXlRpuGyobDxsRHLUd3Bz/IVcmMCfpLSYynTASLpgtDSuhKqEq7yi0JfAg3ByTGRgY0xYWF00XaBdjFNcQsgp0BTYAjvtA/Rf9Wfyq/HH6KPf99IvxwPB777XpAuct4G7We82lxeLB4sGjxKjHisX4xuTCSr//wk7Kadsn5ZjoYfBH6CflT+0m7XLy6flD/wIKCxAEFO4WtBRBGL8bKCLtJ7cnECRwHJAXMBbuFncYsxxCGSQX+BSQDpIHqftd9mPxrOyF7VnrGuVL4k/ccNfe2HPZGdxs3Rnc+dg92SLZ4doN3RLgyuVo7J702feA++T+yv8TBKQKCA4cEtEVIRUhFSIWuRcpGosc+h5eIm8krSmaLjgsjC7FMAMtby2pL7opnihJJigi7h9nH98e0B3eHbIb1xloF1UU3w0CCnIEEAJgAZT/KABb/Uz8A/mV9xb0LfE07YzpmeD314PSqsh7xBjCZb/evmfAx8FqwnG+wb3/wv3SMOIg6VfyN+/254TsRvBX8gX65P4YB/MR7xfSHp0frCC7Ic4kpCwSLtQoAiTZGmgX7xcnGRIdLByfGPoVTxDjB5H91PSi7onnJuRp5HHgNt0v2dTSx9IM1HDX4dpa2knYEdem15zZCtte3f3jBuqN8qf68/+PBWkH2AgXD9gR+xahGScZrRgzGDYaEh2CH9UgvSIoItgi5CF2IM0bdB/WISUgFiiqJwshbSPQHYYZURrgFpAXIhZkFYwUKxMQE20SkQ9sEcYOBQzACu4FqgVvAi0DVgN9AokBJv4t+tb1y+705pjfidb60PzJtMYdxRXAVr59vdq8KbuvusLGMdp93yDpJu135D7ipug+6/XvhPUR+QcFFA1yFWAbxh+FIdskNCrcLckq9SN9HOIXeBmhGfwfuiCYHEEY9hMvDfcC+fr68sfsa+UY5OnfTtum1zDRqtFN0gPXWNk+2s3WntIz017Ul9Y92enfXeVF74b28P0tA2gGiAnEDfMRYxRaF9MWWRbTFl0Zixy6IFAiDSJ5IiUgORwkF88UExUQEzoUfRxuG4kb0x8qG3gZkxnTFqsX3RTOE8kQhRBAD10QUhJ0FuAWxRa5FyoSXRBTCrIKuwfvBj8GMAVXBBr/p/on9invhOTA37HVQ8yjxOu+4rjqtXy0l7T2tP+xcraHzHjcTtu36iflO9hy4fHkTuRQ7qXwPPvUBs4TVh3zItQoWymwK+IxdDAsJSsk7xeVGhQeQSFnKCkjdB/7FisTrAZA/ZzzW+y24TbdUd3k063Tzc1FzfXNg9LK1JTUMtLIykDK8stjz6rRGdwH4vrqhPVn/AQDGAcsCxELzhPdFBYXXRnXGXcY3ByUIlIjdSggJjolCyHOHAkXlBHrDAkGyAdbD8ELJhAsHDQQihP3HLsQexJSEpQIUAhECa8IKgqFENoSdBamHIMgaxm+GmETIg2uEAUMIw7DDOgK/Qb7BYoCCPwn9i3xlOU23SzXWMhWvle2CK/oq5qtBq5Yriqrg7gY0wPXs9+E5H/YatM23U7bdeMC54jva/8RC8EcICaHK7Mt0C6zLeUzGyt/JrYeUxsLIa8iYCzGKBElYhxmFgUMigI09sbrxeI613DXI9GP0UPM1coZy8nLms+az8nLK8VBwibCacoBzdvWfd+/55fwOfnaAWMDVQtxDBkQgBUpGmsZIB0tHVYdOCRLJ6EqdynFJwEjVh1BGLESzQr6BHoAef+RBu8GKgpUE9gRQA/AE38MdQaFB3n/lgEhBK8IfwxvEyIWRBrSHvAg9xx4GZ4XhRC/EqwPJhDVD7gOcQyJCjMHlQA7+m/wHujy3EHT6cWwu3ixYqz/qDWp16k8pWOk8LDLzOzQ+dhX4UHTv83I28HXatz05vLtJP0GDT4f+ycIMAkxaDEyMcM3liy5KJQi3h0HJ54o/DCJLCInFB4TFaMJNf9/8jnov9411FLVHM2wzJzIzcU4xWPGMMgHyAHEibz0u+q9csddyxPYOuBh53Dx6PgPAX4DOww+DhATuxhKHpsehSGuIeQhyCmuKvct9CtaKFAiSB23FjURNglvAjT++fpP/usDPgUmByUPtQz0CVIJbgF2/dD6Z/z0AEQJCg8GFdQX6BtnH8QeWR94GZ4X3hWPFtEVzxRGE4gSQRB2D3EMmwTu/GPxR+i93V7Udcl9vbGz96xop1eljaU2odSekJ6+uzvPvcyu3NDYQMrA1lraZtkp5knpwfn/B2AbZyh3Mjo29jVQM/w59DTVKW4sZx8NK+gs/TEIMI0m6x2TELAJkf119FXogOEj0fjP0shTxVLEZ8AmwhS/ecPiwTLBGLkluQ+8LseJzbTXWuPz5SHyUfcrAscGdg9XFTUZpx0dJBElICaDKCwlmC0tLoIwLC1AKSgiRxx0FjQQGwm9ACH7X/dZ/JL+GwCKAjYJ3QPQAz4F7fsG+xT7LfrOAkYKuA4uFcUWDBlnH00gkyHrHb8b9ht3GKQbdxieF94VbBFPEIIOngZD/6v0U+ei3V7UrcqnvlW1f60VppWhCp/enJKXF5a7sebMTMkm3MncusrI04TbO9it5EzrUfcMCPQaoisdNQ08GTtVNl48MzoDLVYupSQlKRUwMzJ3MiQo3x4NEQwIuv2385fnYN4I0bzLLseDweLBs70Svg+8j8BKv6a9dbhktuW6BMZ9zpnXa+Vh51Tw9fizAg4JsBE2GgUdXiJMKHUoZyhDKyQoBi+7MoUyCTFRK5YjLByBFtMOhgh5/zv6NPZv+bEBSAPRBAYN4gZuAYEFEvq+93/6zfgqAWILkxD4FNcZqxenHXEdWR8AGloXTRdIFBkZCRcKGH4U8xEjDmEKpAH3+aDtuOJO28fSM8ravGO15alFop+fM58bmSaXIq4zyrrKgtqc4g3MndEL3HnU6d8g6WbzYAEkF84k5DK5Of46vjTDN2c5rSmnLjgkCSiaLtYy5TNfKzcjIhZ9C+T+OfkI65DjKdUy0u/J+MacyJ7BJsIjwFzCO74IwHe5g7hEu+rG2s3A1qHlyuVQ7sr21v76BHYPtxYsHIIfBSYiJ94mvSvvKEguCzKFMsUwHi0EJfcc0xZqEAMLfgNe/4z6KACRBjgKcQzjD3ALmwQ5AoL8b/lg+Gj9iQHbCgESwxX+GE0X5RkbGvIZmxWKE7ARAhOnFDAW4BYEFPMRtQzUBuX/G/dn65ng3NeC0VjIjL4utiKuxaZjpFmmF5/3o73Dfc7s0JDj4dp7zUDbqNgX2/3jzO/o+MwJOx08JvMzzzbKMwYvFDjLK+8oFiiUIrAr6y4QNYwu1SmMHWETWQUY/hXzW+yN4ajY29Zvzt3Pa8v7yHvEV8cRxhrD7sAhv6a92MPOzvHTfuAR6DLs+PG1+tj/xwa4DiIWoRkJIN4miCOeKAopriqnLrgwIzCkLKonMiB6GjoUDRFGCv0G7ARuCo4NMQ55EVERFg55CHUGewFP/v39r//7BagMRRITFeIXZBVmFp4XtBQCE0USlBGKExMVdRdoF2MU8hD3C/EH9ADN+DfvyuXm3ZnXK84fxsG9t7eXtOutv6vRpR6jpLxN0lnRreQ/4/jP1dvn3pzZX+aH7g33SAOSGIMgXyvFMI4veitDMwsyVSVDK4IfdShuLLkxqS+VK0Mi0RUeCxACqftG8Lvtlt4r32LXHdaR0vXNXcsKykXN0siQycrDDsSxxPjPANWk3tDpI+t+8VP4nv19AosL4w8wFgIb9SOxIwQlxSe2JnorcS6nLvQrGCk1Ivcc/Re0FJ8PqAx8Cn8MuxjxGK8ZoxoSFHEMLAvFBbEBBgQTBLsH4Q7gFnIVJRjuFkUSwhQ6FPsN6gsFDNAMbRI8Fe4WYxR2D5QIpQKF/uX2he2g5BzeVdfs0JzI/cENu1i3e7Pzsi+u6KsRxqbXudIq5zjnlNTm3f3jatyy52Pxv/iZA0EY1SCcJ5ou9CsTJs0sKiwXIHIm0x/eJg8smi5xLu0nCyF+FNsKywDf+wTxDu914/viG92R24HZTdKd0RDOS9HIyl/M+cckyUDKatMi2bPfCuz66pnxy/eb++X/GwlzDRwSJRhZH+EfDSJkJh8luSiGKncpZygRJasf6BvHFy4ViBIlD8cPbxOMHVwhHCMUHnQW1Q+8CIEFnQXUBsoIMQ6WEpIYhhlmFiEVeBD/EPwOEQuUCAwIcQyKE48WMxgVFoIOZgV0/Cf2y+5J6UvioNxa2tnVHM0WydbCAbzxuYG3hLD3rIu9gtFB0/HkTeyk3jLjmOie483n2u+e9NX9kA6XG0QjTyr0K0kmJypTLAEjUiM8Ho8fsiRzJ+MpSSYjH1oX3w1LBaD+NPbn713lFuNS3mrcMtsD19bTxdE11OvPqdC/zWvLXcvu0XzWot1i6N/qRvAo97b7kv7UBjgKBg2xEsoZUxtlHqIioCFjJUsnPSciJ84kMiCYHDYaCRchFdEV+xZ1F9obhSEZIR4cTRfnEj0NvgltCc0KLAtpD1IScBSPFrYVsxP/EGkPjAxwC1IJKQmLC5QR3RQEFFISnA3RBED9bPeH7rjr1+Ut4IfdWNn60MvMmsfwwcG94rjmsgKrZ69kxw/Wk9wZ7Y7q29/W5IPjz+BE5pTuCvXQA5gTcx5vJDEo+yfAJPEp+SYJIPccrxnSHg4j+yflKmYn6x09FiwL2ADc+W/wt+o15fHkLuFV4F3c6tf/0wzU1NKKzujN1cpOyoTKWtLP143hBuom7VjzOPjN+Ez8NwF0BfYK9RKTGR0bJSDYIociOiXeJh0kwCQdJNMf6hyVGikaZhaPFgkXAxyvIgEjoCG6IDUZOhTTDpgLmAuaDKsOzBI8FRYXPRakEigRqQ3rDFMKPgXEBO8GLAsxDiYQhRDrDLYE4fyf9Yrww+lp5IPjYd/w233Xcc+CyWvD0r+8uqq3hbE9riC+R84m3OXlkews6HHgPuKE5OvgZ+v28ID7GwngFvwffCSmJaAhbyQpI58gXRmtGJgc6x1+JY4nuSjYIjUZIw6eBiH7/vWF7ZjoA+ig5K/lBuHm3SzXEddu1ibTVs+/zbrKdcm1z/TVD95c5NLqAvCq89f2y/ct+rr9BAMqCpYSdxikG4sckSABIzQhNyOUIhUfmx7rHREcHhwNGkQa1xnfHkwoNiveJuUiDxthE5EPBQxkDI4NNxIGFWsZUxviF7ARtAs2CdYHAAk/BvsFGgggDJAOQRBZDswJtAOd/Lz2AvAy7FHm6+CW3tjdCtth1gnSbMwgxz7AEb2QuEyvna8IwEvINNwp7/rqD+dH6GHfKt774hvmkOva+BoIOROpHtEmFyBWHZEglxtFG5MZHxS7GNob8SGmJekkCSBQGfAPDglr/6H2uuzx5OLjx+P05m7nM+T338nc89RX0GvLjceax8nLoNOp2VfheOU454DqKe+x74P0Nvdx+lEAMgYIDgES/RdUHDsd4R9EI2ggLR3qHKQbvhqnHZ0f+h5MH9Yh1yplL3ssnymUIlwYzxSYE3gQsxN+FNEVKRrBHLIbfBPfDZQIjwWFB3kIxAQjBf0GKQmaDCAMXwncAuv6qvMp77jrEegf4FTfY+BR3QrbEddK0B/G4sFUvby6gbdUtJy3qshE1RXi/OuT7bvkzN7b30/cNt0G6sLx4v1xDF8aMR90HwUdpBuhGU4Y4BYtFOwVDxsvHkQjwiUfJd4dwhRnDuwEMPwx9CXsWOro51jqJewR6PTm6+AK2wDVv80bzJDJMcns0APXUd0W4+fmX+a16dPrbO6L8ZD0SvtB/hgHWQ7mEf0Xvxu2HtIeth7QHQ8bNRn2G8EcTSDlIikj9iQlKdMw8TJXL3cpliM7HcUW4hc/F3gZ2RqaHcQeBh4pGkMRiwsJBgkGgwaBBbQDSwXUBuMHyghQCC0DQP3X9q7tf+mI5kXextoy20LckNqp2XDXfc44xam/mL1Cuge3gbe4wH7Prtys7EbwZ+tr5ariH+BD3bPoN+9r9uIGmBPrHSUgryKSGHoaGRm2FSsTVBPTFoQYyiIaIlgnriEAGngQuweg/k71ivCz6DHrFOpg77jrguu85W3eq9qp0KTNGcslyubME9iT3HTiIOk45yDpxusL7aDtBfLx9dz56AEGDWoQzxR9HEgdAxzEHjweMBa5F3oaeBkXIOkkYSRyJjMpSC5LMEgu9y1QIkAg3h3jGCAdRxyMHcIdQSEhHrMcLhXtDQIKkQYqCtYHawjKCBoIXwmkCqMJEwRr/2z3zvDu60Dso+bu4n7gOd+622LXRNVX0FjI2MN0wHO/1rmbtv65ssWC0QnjbO5J6ZfnAOYo3aTeVN8R6A7vJv7cC94VPh/6HqQbtxaTGTwVzxQ8FcATlxtMH/YkpSTbJEccXBjjD4MGkv549tvw/Ott79juIfK77THr8+U23dzXFNAPzQrKHM1D1FjZ29/T4jbmhuVH6H/p9+gL7b/vFvQj/BUFSQxdEEkVAxzKGb8bzRviF90UrxluGwYe6SQuJngq7C/WMrE0sjViLX8mriGPH2UeqR5eIkEhbyT1IwEjBR10FrgOlwoPCl0IYgvMCZUJKQlTCqQKUAi2BBj+Lfru823vkOt/6a3kgeLf4bHe890i2U7Tv80UyLW+qb+2v+O5QLmUwzbMetXb57fqAufW5NHhhNva3oTkEeh/8jkCRwvsFdIeGRk/F/oVchVGE/oVIRWQFzsdNCETJqUkviOjGnUXcw2PBdX9h/dY8xXzFfMw83j28OwI6+Pkk9wm0z/Sv82VzEHTLNeg3BPhCeMy4ynmUOVQ5fbngOop7/30d/7RBBELDRHpE54XJxlmFlkWjxYwFmsZNCEQJGYnCSjcLckycjemNhM3GjPSJ/glSSZQIikjjSZzJ2MlFig4JG4bBhUjDogJ5QgeC9QGRAkbCeAF7waPBUgDF/17+H/yv+8v6gPoNeW44unfHt8N3VbYo9WMzxTIJsKCwE/C4cCpvyPAoct61fPdIOmM6WHnxOES4D/j+OAy7HTzpvmoDFsPTRdmFtcQ1xCED/USAhOcFncYmh3OHGgg8CDBHEQavxLHD3oJOQJ0/GP6TPSh9nX0+vLC8e3qpOdU34TbNdTu0QDVbdX52APfLeAt4I/ij+Ke4wzl2eaC64fu1PQ7+mICGgijCd8NsxP/EMwSgBWzE4AVkxk8HkEh9SMWKDEosiwLMrE0ZDeGM9wtvCrFJ90lVSU/KGYnnCc/KGMlxyB8G/YT7Q1MDgYNzwv3CwIKDAgzB48FjANeALb75fYT8gvtcelh5wfiOd8P3nbb3NfW08XRYM1yxx3FrsK2vx69wr76v3vNFtrL5t/qI+u36lXgD97334Dh5O009lkF0g39FxkZ3RQQE0kMKhKWEnIVPRaJG1YdxB7YIrgf6x3IGOkT9grxB4cAjPqu9uX21/b+9RH5lu9q7RjkXt3N1gvTMtJc06nZvNxX4SLi7uLu4tHhCuSS5MvmtemK8PL2xvyPBcoImgwoEfIQiBKkEkUSKhKqFiwcuB/eJv0ouikGL4g0Wjl/N882TzLjKXcphClzJ8srhytuLAwqTilvJGAbTRfHD8YO+QwLEJgLpAp8Cp0FdQZUAocAtfqu9nDxou4v6n3o0+Kl38vdddoD1wzUXtQqzXjLP8mNx3vEXsPYw/HCmcYL0z7aQuX56Ynn6uiQ44HiUOVb7ODzNP53B/4PqhYEFFoXpROWEogSzxQ/F6sXvhqrH+4fjh6rH+gb4xgNEXwKmwQ0/qb5s/mX+A33RPdM9NrvdOvW5Cbc6td51IPSstbz3dfcHt9c5NTj7uKe4/bnnuN65q7tY/E4+JYBIwVtCdINnA3XEG8TuxBhE1kW9Bp2IOkkySqPMAwzIjg0O383lDPFMEUsayosLdAuBi/6Ly8v1yqeKHsjoRkTFUgUXRAlD1ISNBAuDAYNsAnEBFQCrP2m+eP1WPPO8KzsSupR5mbizt9P3EbWTtOq0dzOb86wzK3KHM2QyenFB8iEymjS1dvW5Mrl4+SJ52nk/ePP6IXtd/XB+ZkDpAqfD70RNBAoEUEQFRbTFoMXMxi+GugbSB3EHiwcfRzjGIgSEgyYC9wCQwBc/hT7Z/wg+r/4fPA370np+uEL3CjdndoX27TgBOBx4HTiROYH4qzj5+Ye6ALneO3e8uL07vyiAKkEngZxDJoMhA/HD8sRBxZ4GRUfECQYKUctJzO1N7c4mjdOOqAy/THJMhcxkTF3MjIxqS+OL+YrqCY0ISAdThhNF90UAhM1EdUPmAsCCmkH6QJuAS/7HfhM9MLxdOu/59flZeFC3Kvai9cJ0oDQ6c6lznjLtc8rznPILsdcwpTDHs6R0qjhz+j36PXvjOl/6THrPeqB80f5fgOVCWwRbRJZFmQVFhcPGwcWsBqqFg0azRvoG2Ueqx8UHhIdvBlND/cL+gQbAML6m/vo+Gz3LPly8nDx0Omh5WDe7dnE2fvZvNxe3SHhZuIY5LzloOTn5onncOiu7fPu7/R/+hsASgQCCu0NSg01EdoSsBHDFeYaPB5GJEApBi/WMmQ3sDxwNsM3czhHLZIynjEwMIUyoDJXL7Uu2iwUJykjAxwDHAcWxRanFKAQ1xCcDfcLXAdZBaIAgvx694T13vKi7krq9ufH47/eXt0H2YXTr9RWz+jNEs9uzeXLJcpSxOXDFMiP0bfZX+ZT58PppuhC5cXiw+l062Hwv/grAh4LMQ4tFAIT8xHnEgcWBBTgFtcZ/hhkHSwcNCHEHowdshveFYIO9wugB5UAwAIY/v39FPtX+zT2+vIX7GjjceAq3svdKt7P4Ozh4OI/4+Ljr+Vd5UHklOV96BbrN++t9fn6MPwwBRoIGwkiDZoMIg1NDw4SnBZZH14iBydTLLMtnjGaN8M3JzM7Nxoz0zB5M1M15DKUM08yti84LDYrYyXGHwYevhqSGK0YFRY3EoUQOwzlCJ4GlgGi/9L7G/eS9dHyXO2a6a3kIeFP3ODZAtZO0+LSI9GP0RDOh8yEysPHhcKdwITKJ9Qm3JXmhOxM66TnsOah5c3nJexc9Wj9LQMiDc8UpROZFLMTwhS2FVkWhhlQGSAdcBypHrog5yM8HjYawxUWDsELtgTQA+X/8P1n/EH+6fkJ9Enyy+Yi4g/eN97t2c7fOd8q3qDk7OHf4VniJuSn4NPiHujf6mzukvXd+qr8jAMXBqEIfQvnCQYNHhOkEssaliO9Incpti87Lpw48DoaM943+DabL/0xfjZTNf8yYTVENKcuOS2hKhcgCSA7HdQXGxrjGOYRDhL8DlAICQYGBE39tvuh9o/zFvTk7dnmX+Y64I3Yl9ah1I7QYs4Sz+jNgsl4yxnLXsMQxaLDscQ11A7V3+GQ63/pAOYb5pXmYugS6Rn2p/rpAnALWQ4uFTkTBhUGFe8XZhYMGXoaRBpHHKYcNSIyIDIgiBriF8sRGgi2BOsD1v6d/Lv+6fkG+9LzYO8F6bjiydxz2dXbJtwZ3Cre99/13mHfZeH44KfgY+BB5A/nq+s58If3Mv2u/rMC5wk2CaEILAuoDJYSnhdZH38mji/RL9gzKzXxMuEwWTAMM2gxUjSBOFU2AjXlMz4wEC3GKIokNSKCH/QaDBlrGc8UbxMZEHMNHQowBVEATf2M+k71dPPO8BntfOdO5OfeWtos14bUZdCO0N3PyMpfzCfL6sbsx4HIAsUfxp7SK9bk3D7iHec4513l4OJE5tzo4esk9Nb+gQU+DqQSURHkENgRbBEXD4wUZhZ1F3Meqx8IH/wfFyCDF1QTdg9TCrkGHwOlAn0CUgEV/LX6d/Vg7wbq4OK/3r3dhNv/3KTeEN+K3xLgbN1e3bzcN94Z3BDf/uTN55TuufRC9oD7rv4M/yoBPgVKBP8H/xAGFVEa5SJOKeEoji+7MtEv7jDfL1sxTTE3NHA2OjbDN9k0uTHCLrwqYyUNItUgcx6/GycZnhenFIUQ0AxtCVYDDP/u/FP4JfUx9KPvnese6MXied352K/ULc/azfTM1co0yxvMesxbym/FrMF7vMG9W8qMzxvdaOOy5+jnWeI+4mnkoeWr66rzyf4LB/QJ4w9ADzURvRH6FWMUSRWeFyIWUxs4G94dxB4XIL4aqhbCFEkMkgeZA4oCef9e/3P7fflc9TrxZ+uS5Ebfk9yC2iLZF9sy25/bT9xP3A/eMtug3NfcutsV4l/m9+ii7kvzlfdI+pT/2gHCAyMFawgjDpkUMxhvJBsr4ykXMUMz0zDsL/oviDSRMYo1FjkuN403bTSqMFcvXyvqJW8koiKMHfccABruFn4UQRBiC68IKwJ0/ND68vbP8Zfwhe0s6Frj/9xK2RrUY8+JzWLOUcz+yoLJnskExqLDe8SqwAvCJMla0n3Xm+Go4eDi4OLR4ULl3um/7zH0+vsGBBoIBg0XDzEOlBH1EjAW7hYZGf4Y2RrcHJodBh75Hdob0xYtFD4O6gtNBhME6AEcATT+YvmJ+LHvJu1R5gnjRd433ijdNt1D3U/cot3J3Lzcdtte3f/cot3E4XjlIurm7kvzM/Ue+Y/8lP8AAGYFTgcqCjwV4Bb8H10qhiocLDAwqjBLMOsuhjPlM3w1xDj7OJA56DVeM6cuRy3VKaYlAiSsIBUffRyTGcMVzBKBDfQJdAUAAPz8wvrj9TDzRe/E6kTmH+A03B/XhdOazw3M9MzXyzbM4cldywjJw8dfxHbBL78tzwzUatzL5i3pG+aD46/l9Oaa6ezyHvmG/zYJdQ5bD2wRKhKZFHIVhBj6FeUZehpkHRcgJSBPISUg9hsVFtsTBg3IBwwI0wXsBKUCav48+5X3cPFb7G7ngeIB3szefuAD30jg99+/3jbd5t3L3TTclt4Q31zk3Og07enwdfTm91T5nv3z/zoDkQaSBxkQJBeLHCQoXyuYLcUwPC+AL48wMzKxNBM3GTsoPGw8WzpwNkEyxC/oLCUpuSi0JXsjySFzHqEZWhe/EnMNzQrRBOX/nv3a+EL2S/Oi7s/okuSk3lvb29b90qXOis6wzCfLbs2kzQjJW8qryaLDx8HRxzfVw9jg4hntl+dE5mLo9uc07RHxzfjk/voEFw95ES0UchUiFuAWyhk5HIgafx1zHoUhoCHMI4ciTSBgGwkXsxMIDn0L5QgaCKoFigIJ/fn6rfWX8J/sAud147TgBuFK4Vfh0eEf4BDf2t4Q387fYN4e303jzecm7TrxWvTy9gH4QP2i/8AChQcpCTsM6hTCHRQnbiy1Lkov4jGRMdYyEDWdOcQ45jwuQPg/mT94OyA3ADTWMqowfS2iK7koVSUQJFsgfBvxGOcSZQ1QCDwEyv+4/G74kvXC8d/qd+Tz3YHZhtSC0VPNocs3zU/L1MnGyRPHa8NbwdXBb8X4zzvYJtzU40Xn8+XI5JTl0Oko7l/3vQD/ByYQDRFwFD0WxxcAGkoeZx+1HdskmSWcJzQqWynVKX8mvSJIHeYaLhUoEYUQkQ9KDUQJxAS7/gP5MfR57h7o5+bg4t/hCePP4C3gb98c3nbbGdzw24Lak9yZ4KDkEukL7R3wdPNr9i36j/wM//gDXAfcC6cUhhlrIhIuKiz8MIs2NTPHMc017znXO4o+M0PiQtNBckBPOy43zTUmMmUvxC9iLXcp0ie9It4d1xlJFa4QtQzTBRMEvQAv+2L54/Ve7gPo4OI23QjaetUk0vrQcc/azaLMRc0ny1vK7cj4xkHCjsjc1/vZ++LH7BHoA+h/6Z3rGe2q89z5GwAPClQTnBbgFgoY/hjlGX0cQCA+H/8hzyXgJ7wqkinyKkglnyADHGkYbxM0EFER/A7SDR0KmwQoAIz6t/MN7knpM+Tz5RrlCuTx5BbjfuBg3lTfUt5d3FHdD9464JfnTezm7tHykPRd9g/4Mv15/ysChQc7DGQVlRraI9kreiuJLP0xCTGPMG41WjmuO789GENZQfpApT6COTo2ijVeM/ovgjCaLhkqkCimJUwfAxzgFmwRLw2FB98EAwJN/Yz6a/aj74zpgeIo3UnY/9OO0BTQSM/1zQ/NNszSyB/GAsXhwA7EYs6R28jbP+Pc6FTfreS85ZfnHO/x9SH7cQMuDMsRbxO2Fe4Wuxh8G2QdFyBqIX8mxiiwK28tCilCKrIkgB4sHNkatBRLFo0VeBB2D10IbgGS/lb6f/Kg7SLqvubn5inm4uMK5G/frtw23Sbcadvg2RfbG93A36boc+pA7B3we+/48QD33PmC/BACCQZWDJkUKhtIJbwqFigeLXYxgC+DMX838DoqPY1AaUMyQhNAXjzsN342+DYzMk8y8DEQLfEpnCc0IVQcyhkCE6sOYgvgBZkDAQEV/Nf23fHS6p7jsN0+2tnVm9CKztrNX8z+yk7KLsfbxRrDGsP6v37GqdAp1XjcvuZB5JDjWeKS5ALnru2H99b+uQZMDkUSSBRwFKsXThgdGy8eTSAsJagm7ygcLF8rRSwxKNoj0h4DHMUWmRRwFB4TbBEvDWkHYAHS+5D0ve4X7Nzoy+Yz5LnjtuEf4L/extqO2ZDawddi1xfb8Nvb38jkpOec6qLubO5V8Rb02fcJ/a//uwcXD6oWxh/OJBMmWykbK+gsti9DMz04vDsQPvpAM0MGQKI8aTqmNrQ2sTRcMnYxPC84LO8oiiSrHwIbwhTVDy4MGgjsBCoBuPxF+EjxkeyI5jnf1Nr21t3PKs1szOXLG8xnyZrHfsb/wiC+v7wqvMjK/9ND1Anj1+Uf4PffLuGP4gPoQ+7I9YkBUwrtDRwSDhKnFGYWyBinHWAbth44JDoluil7LBsrXSrDJjwetR16GmASVBNJFb8SbBHBC2YFDQA5+RDwau0v6r7m9Oat5KzjEuA23azbxtrS2UfX59U41vbWuNou4TLja+VW6e7rF+wC8DzynPN/+hj+uwe7EPoVfx00IbIk3iYAK7IsjC6FMo44uTlGPo9BV0BUPnk8nTl+NmI2UDPuMCYyzi3ZKyUpliPtHv4YsRLGDlMKgwbAAtgAV/uE9aPvBupy4fDbLthO0wbQrsv8yeDIl8XJwm3E88Nzv2K98rrZu6vJIdBT1hLgz+Bn2oTbydwu4UXnLfHB+W4BbQnEDU0PNBCuEC0UMxggHS8e8yKoJgcnNCpsK9cqrSkrJN8evxvlGewVkBcYGHAUeBA4CqUCnfz+9W/whe1W6Yvoi+jx5C7hv94j2qbXi9fM1b3UodQ11ETVZ9qY3+vgM+Tz5XznfOe46xDw+PEq+DX/iAkqEmsZwRw+H+IgriGLJW4sqjBhNdQ5lTzdP3E/pD1DPDM6FDjcNn83bjVfNPAxmy97LLkoRCMvHoQYvxIWDrQLGggTBKQBMPxo9CbtD+en4HXaD9bR0EXNT8uqyC7HH8bZxP3B+b73vR28Jbm0tW3EAc380RfbZeF43Bba1Noc3oHip+lm84P9JAbPC10Q1xD/EIgSbxOXG7IbMR/AJO0nASxRK+YrOCwgJjEfYhwqG/oVMxjHFxUW9hOcDaoFlP9T+LTxx+zQ6QPopOf+5LvktOCs23LYK9Yn1J7S/NFc09jUEddP3Drgm+GB4mnk1+V96Ovp2u+69SP83AK6D4kb6BsFHWAjryJcISIngC8QNRY5cT/HQp5C+D+tOj45+TcTN0c2OzfDNycz1jI8L1spAiR/HTYamBMxDpgL7wYfA67+0vvg853r1uTy3FXXkdJgzQjJB8iByG/F+Maiw3++sLuqtwK0K7TstknHW8pr1EbfsN0s13rV6NYj2o3hhOwq+PUBDgn7DboPTQ/zEQESPBWyG5gcbSNmJ3gqBC5XL0guayphJDEf3BwZGUEYiRuVGsoZqBU+DnIExvyf9Yfuhe0j68PpVejz5cXibN2E29nVaNKR0t/QctDU0vHTK9Yl24fdEuDP4HTigOF45QPose/c+SoBmgxUEwcW5Rl6Gh0bCSCrKFQt2DMZO7E9sz4hQN0/ojwnOyg8ujoKOmw8fzdWNwQ2uTF+LuMpoCEDHOAWDhIKD2ILJgenA3b9afVF727nA9+o2LvTIdAPzZ7JScfbxRjCVr6mvb67dbgHt422ebKGuoTKK86R0pDahNsM1PHTn9uw3VDlOvGy+LMCRws9DfwONRHmEc4TQhlkHYMg6SSfKaIrby3aLJounymxI0Ag6hyLHF0ZfRzlGRUWbBEbCVYDdPy89qLuaOwj6zvps+hQ5S7h8NsU2WvU/dK50vrQctAL01LVtdh220LcA9/a3nHgWuNk6XTr/fRM/FYD8A/2E4AVRRtxHeoc8yJPKuwvVTahO1Y/wj9lQBA+8jutOkM8TjoNPAE9cziBOG41+C6iK9EmWR8dG9MWvRGpDWEKEwRsAMH5tPG46+LjbN1V19TS986Ty9TJgcjPxoXCPL+wuwy6Irfstli3dLf8wGPPb86l1gja+djx09DYNt344Hbs7/RD/+IG1Q/TDpAOrhA1Ed0U9BpoIGAj1yr1LHIvVi4QLdcqfyZrImcfJSB/HYwdjh5TGzAWWw93B5T/I/wk9OnwQ+4l7Lrsc+oO5krhGdzA1gzUa9Ra0nbSN9Wx1fnYGdxs3eTchdxj4N/hM+T+7NLzNvfz/44NTxA1EWAbwRw7HaAhdSjOLV4z1DlWP7hBJEIuQGI+mD4bPP87eTxiPqI8RT0nO5U0FTBpKZYjZx9FG9MWEBNzDTUI0QR3/jT22u8P55vh79pS1STS6M3SyKrIPcgpxEDBWL9puVW1H7XnsxyzUMPJy4nNuNrk3PDSndGJ1nzWD97T68j11v4kBiMOTxBND4UQfBP7Fr8bnyA8JrArHi3JMmsz4jFbMQEstibYIikjMR9eIg4jMiCdH0kV0AzuBdX9NPbG9KjyHO/A8CbtVega5fPdqNhu1q/UXNNa0gDVK9Yr1p3a8tx53cncVeAH4v7k4uxv8MH5zgIPCkAPthW7GPIZcx5EIwopZS/PNuM63T+sQvFDTULfQDxARj60P2M/IkG2QBA+8ju1N/EypCx/JjQhshufGG8TMg+kCgYE8P0q+Drx6ujg4tXbRNX60GPP5ctmyLLFh8N3wgW+J7ppucC0bLJjtcXI6M0fz4fdadt51GjSMdqE2y3gee73+bMCoQg1EdcQ1Q/YEbQU9BpYHlIjqyiMLpouuzKjNP8ydzLXKiUp9SPKIlwhHST1I4Iffx32E6kNMgbH/Zf4ZvMF8o3yPfMo7nDoaeRS3jvY9tb319nVTtMd1rfZPdl53bzczt8q3kvi9udM61Dug/QAAKkEwApSEgoYyBgqG+IgFCd6KyMwIDdePDxAPkFmQTJCgEB+P6c/pz8fPzxAfj8DPjM6zTU/MSgrfCRBIXAc7BXLESINownpAoP9NPYO7xHouOIm3OfVx9KlzpXM8stmyCzGNcM7vgy677jiuEi1zbyA0HLQOtcm3MncudLZ1cbaKt7S6mTyUP8yBsMM8A9dELsQYBJBGBIdsSMsJcsrmi62L8kyQTJrM48wHCwwJ/km9SN3IVUlQSHTHxIdpBJWDOIGJP04+F32qvOo8lr0e+/e6ZDjRt+r2vbWtdjD2CvW4Nkm3IXcKN344OnfWuP05vrqUu/u88f9QwDYCKwPSRW3Fg8b5CFtI5Mq3y8rNSU6Kz5lQKpBJEJmQbhBgUGBQcRAgUFjP1I91zsHOKEz3C0lKecjWB7iF/US7Q1OB84Cav4b94rwSely4QrbXtQh0G7NZ8kkyQ7EiMRZwCq8QLkWuGG06bQ6xmLOacod1n3XhtQk0mHWs98a5SjuufQDAhgHcAtMDhoRqBVXFdIesSP2JKsoxC8jMPwwfjYsNo030S/NLKIrWij2JIslSSaUIu4fGRn1EvkMjAO4/G/54PPj9WbzwPCd66/l7OHj2/zaBdgg2F/VfNbQ2ILakdtd3ATgFeJr5SzodOsB77n0+vuNBHwK2xMWF58Y3h2xI0snTyqeMTo2UTxGPtNBTkMkQiRCMEE+QbQ/ckB9PpU8NDtMOSs1xTCwK4slZx+7GOcSWQ4PCvoENP5H+bbyMeue4xzeOteC0TnOAc2tyhPHvsSDwfe977hAuY+3ObTEv2DNJcoL0zTczdY+0SvW9d7n3lXo1PQL/hME9AlREVERYBKlE3gZjx8LIQkoHi1mMOwvDjQQNcoz4TChKjYr1CjpJM4kMCcaIhQecByYE0AP7waG/+37d/X99IHzSfJP7ZjoKebM3v7b7dmo2InWU9Zm2SXb/9w53yLireRc5A7m7eqZ8bn0j/yKAugKDRF7EqEZqR53IRwjTyrfL+QySjhCO9w+pT7fQPg/ij6zPg08hTsXOu04czg7N9YyLS77J1wh5hpwFKwP3AsLB0UBxvwq+EbwYuhm4k7betWp0B7OJ8sgx+nF2MNAwbjASL4zud21aLiqyP7Kpc7S2WbZHdZa0kLcb9+75Jbv7/QEA+wEqQ1ZDogSExU6FKkeCSARJdEm2izpLdwt5TNDM4g0vyzZK5AoSCUBI0MiOCRWHQMcIhYqEpgLfQLH/a72qvPS8wTxb/Bz6uXlwuCw3WrcLtiQ2szV29bg2ZHbHt+z30HkTeNT5xfsVfHW9S36KADCA3EMeBCPFlQclCJ+JbkoZS8yMfMzmTaFOxw9pz+qQahA0D/mPGc5+Tf4Nh82sTRPMs4ttyfxIXwb3RThDlIJ6wOs/b/4rfWu7crlOd9a2oXTb87+yovGQMGswVa+LL0dvAy6z7V8tN+/mcZjxjfNrdPw0hTQEdcb3X7go+YH86f6r/+UCJwNFg4qEnQW5hqPH4gjMShFLN8v4TAzMvMzHTWPMLMtsy3jKagmEybAJMcg3BzjGOkTnQ4kBr8BZfsY9e7zLfEB71jqDOWb4XvePtoH2SzX89Sx1S7YZNgm3G/fsN2Y31DlWeu36nTzX/eA+9wCCwdnDqUTURqzHHwk4ShPKt0unjFSNC43bDx7Pcw9fT43PTQ7IznNNXo0yjO4MH4uNitIJasfDxvAE4ENbQl9Arj82fcJ9JPtRefr4MncmdfF0b/NIshjxj7A4cBowba/+b5TvB28DLpJx73MT8tr1AXY3the1Cre4OI56Nvw1/YeAgcFOgtzDaAQmRS2FcQeriHeJv0okilvLQEszi07LrkxLC3FJ+EoLiaII/oeqR6wGmYW5hH5DB4L5gAG++b30vNV8aLu5O1h50viH+Bq3MjbTtvS2T3ZZ9pq3InePOH331rjDub66vryXPXO+YX+wAL4Ax4LYRN1F4scNSIkKIQp3C1LMOIxsTTBNp05oTsLO4Q67zlGNTUzlDPVMVcvRy1mJ/0g3BxLFqIRtAvvBr8BZ/xr9hHxq+t04pXdi9dS1VfQlcyax0/C1cFUvXu8ibz0u422t7csxvnHgsmP0STSM9Od0QXYKt7I5I7qVfGF/mwAuwcPCtMO8xFvE7gf0B1wJWYnWiiVK0ctnTBZMNk00C71LGkpmib4JRkh/SBYHjgb7BW9Ed4M3wQM/7/4d/Xv9C3xve7q6JTlcuGu3JPcdtu12M3WjtlY2dXb6d853+vgyORK6lDuM/VH+RL6kv5XBG4KkQ8xFy0dXiJzJyUpOy4JMXYxKTScONU6yTtsPLo6CDkfNoYzDDPTMPctNiv2JFgeXRmMFPwObQn6BEH+sPfP8THr8+WY3/nYNdRy0L/N3cZ3whS/k7pEu/65hLk/uFi3r7rjypnGNswO1UHTzs6S0wPfLuH36EnyTf1GAmgGCA4+DisTihPLGg4jLCW6Kdoswi6MLu4wyTLZNP8yvyzcLZIpfCTaI1IjnyDZGmkYbxNnDo8FlP+n+vvzPPKl8OTtQOx35Izglt642mTYptfP12HWpda42szemN833gnjfOdW6UbwMfRs9936ewGyCpAOZBXcHFsg5CEHJ4ksPC/TMBoz+zh5PDQ7lj3YPDQ7BTcbNGE11jL6L/ct/inOJMYfyxpIFJ8PdwfaARf9hvbO8JHsU+dS3nPZDtWb0JLK9cRBwkq/VL2ju869XbpXts+1Z8DGySDHL9Ba0p7S7NAA1c7fkOMl7LfzUP9uAVwHWw/cC7sQ7BWnHZYjqyiVK6IrgjADLY4vazPnNPEyPC9XLwopcye0JU0gJSBuG1wY+BQ+Dv0GewEG+570yPVM9KPvMuw25mXhsd543GnbCtuB2UzaMtsq3hPhE+Hs4XrmJeze8p/1pPhA/Vz+QwCkCqUT0xYUHgQlByd3KfUsCDB2MRA13jcZOzc9DTxzOMM39DRoMZEx7jCyLD0ndyEdG5kUMg+MDFIJNgBZ/Mv3ou4C51niot1H1/HTxdH3zj3IkcHcvWm5a7pouDW6AbyPwEPMtsf0zAvTudJIz73UzN6l32frpfD1+F4AZgUuDMYOVRT4FDkcJiFBIYMohioeLYwuQTJTNec0UjSYLfguvCpyJvkm9SPYIggfcBxLFigRmAu0AygAVvpg+OP1IfIc78HoU+cW44rfVN//3DLbCtuQ2ibcVN/C4M/gROaz6AjrE/LS85/13fqv/y0DYgtGE6oWfBt5ItsknCcPLOktLy8pNB82PTgLOzE54Dj5N/Y1rzOtMlsxsy2TKjgkhSGYHDAWyRCoDF0INgCL+f71zO+X54HiEN8+2ojVctDXy93GQ8PhwCG/pLyHu065lbtJxz3IgskM1IXTj9Hf0O3ZYd/C4H3o6vG4/JL+3wRVC8YOARJvE0oeJiGxIyAm7yjpLSosGDJuNR01MzLhMNMwTinGKIslsiR5ImQd3h0MGW0SLgz7BdgAZ/yM+jb3M/Ud8EDsBenK5cjkFeLC4M7fVN993zzh0+J145Xm4etI8Y3yuvXO+WP6gvykAaMJCxAfFFEaNCGZJcIlhCk5LTsuMjEpNEc2IDcfNpU0UjRQMz8x7jAgLiUppSR2IIgaVRSHEfsNrwj3AjX/YvnP8ZDrJ+UG4brb99fW0wjRrstjxoXC/cG4wG+9fb3ZxBzNV8dHzuTT5NPoze7Rot0E4BjkaOwA9+b3I/xjAwsHLw3HDz8X6Bs+H6Ii2CJmJ/0oTyoXMWszajK2L9EvsiwxKD8o3SX4Jb4j7h/CHXUXfBNkDDUILgQBAVD/0vs29wXyYO9b7APo6Ofb52vl4uPs4Y/iCeOD4/HkfOeC623vM/UM9sv3tfri/Q0A4AWpDecSxxd8G+0e2iNzJz0nKiwXMaowyjM3NIg0QzPWMp0wuTGsMfguVi7RJuQhPB5cGLMT4Q6ODQwIAwL8/Cr4IfKd68vmxOF53SLZNdRl0MbJzcVXxwHEqsC6wRDF0dD5x/7KsdWI1c7O7NDY3fLcgOEP51Lvyvay+OL9LgQRC3wKXRDxGAkXwh2dH20j6iWcJ4wuxC/hMNosLS4ELqgmTimoJn8m2iNPIbog9BpaF2AScQxtCXQFmALl/9L78vZa9EnyivCR7OLs0uq/5ynmlOWJ51PnR+iA6rvtSfJa9IT12vjS+6n7DP/fBJQIFA0qEjEXfBt0HykjYyUkKGsqUyzpLYwuci+OL98vPC9+LnIvVC1DK94m5SLtHq8ZZBX/EBYOHQpLBW4Buv1g+C7yQe3q6MfjYd/I20bWd9PozdnMe80IyYHIIsj1zSbTy8wL0/nYU9Yy0vnY9d4f4FDlcOjA8L73Ofmn+n4D1gfuBXYP2hJjFMoZXxq1HQkghyIUJ+MpqyhyJncpcyd7I4okUiM4JDQh0B2aHcoZ3hXwD9AMcAvxB+wEigIoAPn6svgo9xn24vRw8YrwEPDJ7UDsRe+X8K/up/FO9QD3Ufcq+C/7uPxD/6UCDAgRC44NuxD2E5AXRBqYHE0gvSLnIwUm7Ca2JnAlzyUuJgQllyRjJeQhwh0PGxgYVBOQDuEODwp0BcQEDQAv+4b2FvRF79/qZOnl5XLh5NzS2VLVJtMz0/zRdNEY01HdYdYR15beydwv2SLZH+C44qHl6OcN7oP0JfWk+Fv9HAH3AmgGUwrACuMPDhLaEoEWhBibHo8fnR+6INIe1SBHHKYcAxyYHIkbkhjKGQkXzxTmEe0NPQ1hCncHdAVUAmwAav6A+xT7ZftX+3r3OPjm9w33q/Ti9AD3Dffa+AX68P1D/zX/lQBGAsUFuQbZCcMMxw9FEpgTdBbIGAAapBsUHlgeFB6CHy8eiRsCGzgbNhpCGQkXwhQ3EoENHgsOCesDHAE2AMb85fZd9pD0KO766t7pvubF4rPf/ttO2yLZ2dWx1brbOuCp2b/eS+LR4ZXd595c5GnkKuf253zwMPNM9OX26PhRAFz+ZQQmB5QILAthChkQqw7zEVkW4BaTGTMYYhw2GuIXMRe2FVoX9hNJFToUpBLJED0NqQ1HC6EIGAd1BtAD2P/YAE/+Z/yA+9/7JP2O+/r7+vv5+mL5OfnE+wj8aP2i/2wAYgLOAnIE4gahCHwKZAwlD1ERRRJFElUUVxUwFjMY/hgnGeMYdxgHFiEV2xMeE9gR0g1YDd4MMwcSAwYEbgFz+wj8jvuT9nTzEfHY7nTrVei/56/lZuLO3+vgv9642oXcTePI5BzesOar6+LjVeBT5xTqeuap6r3u+vIk9Pvze/gI/OH8Gv88BJsEdAWgB9QGXQhGCugKxg7LEQ4SvxKlE3sSlBEZENUPQRCQDpwNPQ3DDKQKJwhdCGkHdQaPBUoEEAIbAP/+qvww/E39gvy4/Cb+dv3G/EH+Tf1M/FD/UQCwAG8C3AKnA+wE+wVpB1MKVgzDDJEPTxANEXkRYBLnEh8UmxWNFXIVPBXOE20S/xBBEGkPTA5kDDgKAAm4BZYBNgA2AE39i/np+bL4MfTq8VTwse+f7GXqWOqa6eXlJuRf5vvip+DT4vPljOl45bPon+zr6YjmIOlc7Z/s1u1t7yLzTvWQ9Nf2pvkV/J79UQDoAb8BEwSzAi0DWQVNBmEKLAuYC3MNPQ3PC30LBQw6C+gKlwo4CmEK1gcmB60HZgVZBXUGaAaZA8ACfQIa/9b+ef/l/17/vf9uAdj/lP9sAFEAegC/Ad0D0APfBCMFdAXgBZEGUgl8CpgLWA0jDrgOqw7wD58P8A+HEYcRhxGFEP4P7w49DdAMfwxkDB4LiAkaCOAF3AJQ/8r/ov8h+5r6uPym+av0QPW59OrxAvA17gHvoO3r6VbpZeqk5/PlA+g+64Xts+iC6x3wn+ym6J/sVPB27A3uOvG28pzzWvRA9VH3i/kF+p79Qf7G/DYANf/W/hsAOgOPBWUEkgfYCP8HhgiGCHkIrQfzCJQIUAhOB/sFaAYVBWYF7gV1BtMFWQXsBEYCAwJSAfQARQFgAR4CzAGKAswBbgGzAqUC+AM8BAcFkQbsBI8FnQXHBrsHeQhTCugKEgwUDSINSQw9DT4Ocw1ZDqsOFg4vDQUM6gtHC0cLUwqVCaEIGAcXBvgDsAANAGABu/4+/Mn+nv0s+b/4Kvjm9wr1g/QW9Dzy9vCv7pPtru1Z6z7rTex47VXxDe7i7PbwivD+7Gjss/Af8f/tKe9V8bbyIvP68rn0evdH+X35Y/oU+wn9qfvE+2j9KP8DAnsBRgJLBUsFMAXgBfsFCQbUBiQGPgUXBoEFIQRKBLYESwX7BewEjQR0BesD6AH1Ac4CEgPMAQEBSANXBBIDEAKNBDIG0QTEBGgGdwf7BewEjwWeBpIHyAeGCNkJ6AosC1ULiwtwC+sMjAzqC9AMSQzBC1MKHQqkCioKRAm8CK8INQiBBbQD0AMDAvP/NgB6ALv+GP7x/mf8Bvsw/Iz6LPk5+dn3k/ar9Jzzm/KX8N3xzO/M77Hv2O6n8S7y2O5+8fvzBPEB74rwE/Ir8M7wSPEi8xb07vMx9JL1o/e+96T43PlI+tD6L/u2+477NP4NABj+9ACzAgMCHwOlAkgDVwTrAwQD+ANlBDkCBAPCA6kEBAMEAzAFgASzAtwCqQTfBGMDzgJmBU0GzgL3Ap0FaAabBCMFaQfxB54GdQbvBuMHyAe7B4YIRgpGCg8KRgrNCosLwQsDCywLcQz3C6QKHQpTClIJNgk1CNgIJwjUBgsHgAQHBesDBgQrArEBpQI2ABsATf3w/UH+VvqA+wj8IPra+B34RPcn9mj0B/P782TySPE68XDxJPQt8QTx4vTR8h/x6fBy8n7xBPFw8XLy7vNL87fzhPW69Sf2Afjo+FP4Lfrr+gX6p/qO+yT9x/13/gAAegDMAQMC2ADpAs4CfQKlAjoDbwJvAgMCNwEfA28C+AOzAiEESwViAusDVwRlBKcD3wSpBJsEgQU8BEsFgwbuBT8GTgetByYHkgdoBk4HuweSB6EIrwiVCc0KNgkdCiwLiQo6Cx4LpAoeC2EKyggOCUIIhQfzCDMHdwcYB54GqQSABN0DBgQtA5YBHwMEA3n/2ADl//P/4v0Y/gv+7vzf+9D63Pmy+Ib25vdQ9gz2TvW59Ez0nPPU9Mj10vNM9Cf2TPRY80vzZvOP85vyCfRA9cj1M/V39Sj3a/YP+Hv4pPjO+X/69/n5+oD77fus/dX9yf4AAGv/HAF6AFEAUgEqAegB2gFgARACewHYAJgC6QI6A9wC+AO2BGUELQOnA2YF6wNjAwcFPwbEBFcEdAV1BpEG7gXWB6EICwczB2sI4wd3B68INgkOCUQJOAqXCgIKfQvoCtsK3AtiC6YLbgo2CR0KGwn/B2sIygjWB+MH7waRBrkG4AXfBI8FqQRLBYwDfQLOAs4CegCHAOYAKgGv/8f9//4I/Ez8Bfq/+Dj48vbj9ZL1kPSD9Hr3uvWQ9A332fcz9fvz4vRp9Y/zqPLu84P0g/Qw80D1GfaT9tn3bvgs+c75p/rO+QX6f/qb++H80vtc/l7/a/8NAKIAOQLoAegBVALpAgMCsQFSATcBlgGWAdwCEgM8BIEFEwTEBFkFgQVyBI0EWQXsBPoEBwWNBJ0FJAZNBgsHuwcACYYIuwcMCKEIGghCCHkIsAnZCTgKRgrACowMRwvcCy8NEgyaDCAM9grMCdwLNgmICcAKHQrACl8J5wnKCCYHowl1Bk4HxwZoBgkGmQPEBEoELQP3AvgDvwFUAg0Ahv8o/xf9Pvy2+3/6LfqH9zj4RPdQ9r73svjK9g33R/lE95L1GPW89gr1WvTU9DT21vVp9V32hvYP+G74Rfg7+jv6wvrr+mX7FPvt+0D9JP00/l7/QwDK/5UAzAHaAUUBKgFjA8ACNwEDAr8B2gGxAbMCcQNXBBcGVwTRBJ4GjQS2BDAFZgXgBYEFgQWqBQkGdAVNBicI4wc2CW0JlQnYCIYIlQmwCV0IRgrDDMwJzwuYCzsMSg3PC3MN/A5zDS4MFA35DBELRwvoCkkMpguYC5gL9gqXCswJDwoRC9QGiQoMCMcGgwZZBT8G0QQ8BCMFSgT4A0UBYgL0AJL+XP6R/Uz8SPo8+7L4y/cB+AH4s/kq+FP4Vvo5+eX2RPej95P2DPbj9df21/YZ9ob2Ufd693v4i/kS+jz76/pz+5r6V/uO+3T8gvyR/fH+5P6U/xsA2AAqAb8BlgGkAYoCsQFFARwBNwEqAVQCfQLpAj4FuQbdA6kECwcjBSMFqgUXBrgFFwaBBdMFXAesBrkGAAkbCbAJ9AlECfMIDwoACW0JYQrACkkMzQq1DC8NtQy3DVgNFw/EDQgOWA1xDNAMwQt8CkoNbgovDWILjAyXCnALUwqkCswJzAlTCuMHrwjKCI8FQQfFBTIGFwZlBOwEHwNUAtoBUP9r/wz/QP0I/DD8gPuy+Jf43Pnp+Uj6ffm1+kr7YPhT+FP4Kvg291H3Dfds95X3KPdE96P3YvlH+Uj6Bfo8+xX8cfrd+pv7CPzu/An9C/7k/sn+//6U/zYA2AC9AFIBYAE3AdoBlQCHADcBNwErAmICBAOPBbgFBgTsBJEGnQWABCMFuAVNBmYFFQWDBtQG4gZBBxoIownnCRsJRgqUCB0Ksgr0CcwJBQwUDXwKjAxYDcELdQ4iDdAMqw7EDVYMxA0FDKYLmgwDC9wLcQwuDOgKOwxGCgMLUwodCioKXwlrCL4JJgfYCD4FngbFBRUFxAQuBLQD2gEeAq///f1r//z8Ffwj/GX7f/r1+Kb5mPn5+r/4YvkF+lT5pPiV9yr45veu9hv3OPgN9/T32few9834LPke+WL5mvqn+oD7SvtX+7b7j/wX/Qn9T/4m/tb+DP+U//P/yv+v/3oAegAoAEMAAAAoAEMAXgDoARACSAMTBHED+gS2BKcDPgVXBOsD3wR0BT4FMAUyBmgGqgUmB1AIAAnzCHoJegkACZUJKgqwCdkJ9gpkDH0LzwuBDTsMBg0GDSAMgg7BC6YLCA5rCAgOAgo4CmILHgvBC9kJtAuXCq8IpAoOCW0JGAeJCnUGaQfHBoEFJgc8BGYFVgOABJkDogC/Adj/1f1P/u37gPsh+0j6Y/rZ90f53PnB+R34BfpI+sv3X/d694f3k/YM9v71hvYN93j2UPaG9ir42ffm9xH5pvnc+bP5Evr3+Qb7PPsU+6r8QP0y/fD9Jv53/lD/r//W/ob/sACG/4b/Gv+U/8r/5f8oACsCcQNjAx8DPATEBCEESAMGBBMEtgRKBNADBwUwBXIEdQaqBf8HrwjYCLwI8Qf0CfEHXQhdCIkKvglTCugKVgyJCsELIg0FDC4MIw7qC7UMbgq0C1MK5wlGCjoL6ArlCBELAgpGCtYHRgoOCQwIoQhNBmsI+AO4Bd8E+AMGBIwDBgRgAfUB5gD//nf+CPzh/CH7Ofm1+m/5UPay+FP4A/n09773R/mJ+OP1rvZ49k71GPUK9ZD0afVA9Rj1XPXI9VH3sPc4+EX4Evrc+b/4Ofmm+dz5Y/q1+qn7gPsJ/TL9F/0Y/nf+NP5q/jX/kv79/aD+W/2e/f/+yf7J/ocApQJiAlQCswLcAqUCHgLaAR8DcQP1AaUC+APpAi4EIQS2BCYHDAh3B/0G4wcmB6wGJgeFB4YI2AiVCfQJYQr0CegKlwrbCuEOKgpiC/YKygiVCYgJrQfMCZQIRAl3BwAJJwjHBrkGaQc1CHQFjwV1Bt0D0AO/AXIEAwJuAeYAvwHz//39T/78/Iv57ft9+fT3DfcN91D24vST9tf2hvaj9wD3evdE91z1hPVc9Wj0ZvPF87n0j/Mw8z/0dfR39UL28vaj9zj4ifgB+Dj4ifge+W/5LPnd+un5+fqO+/r77fvG/Bj+j/x3/lv9QP3G/IL8WfyP/PD9uv0M/wEBYAEBAXsBVAIQAkUBvwHcAgEBAwL1AZYBwAKYAowDIQRLBSQGTgebBJIHkQb7BV0IJgcaCKMJkgdGCsgHlwqJCpcKQgi1DHALNQjnCaMJ8Qe5BtkJCwd3BxgHvAgJBkIIQQf7BU4HfgPxB2ICtAMeAtADYAGS/mABd/7LAJ79WfwM/yD6IPrp+ej4rvaV97r1CvXv9Hj2kvXS87r1hvYW9J70aPS59IHzw/LR8uDz7PJ08+zydfSe9Mb0UPYn9r73KviV97L4HfhU+X35EflI+i/7IftK+z78j/wy/TL9Cf39/YP9QP2D/YL8gvyC/Lj8dPyR/U/+GwCG/ygANwEqARwByv8BATcB2P/mAAEBiQGWAVIBEgNIA6cD3wR0Be4FWQXuBUEHQQfTBf0G7waFB4YIGAcCCgAJDwo6C/EH9goeC1AIGgjIB60HrAbgBU0G0QQzBz8G/QbUBvsFjwX6BIwD0QRFAUYCEgPw/aIA9ADt+zX/j/yC/I77ffli+fX41PR49lr0JPQJ9Gn1aPT68u/0k/Yi81r0g/T99An0PPLg80z0mfEu8kvzgfNM9Ar1Qvbl9jb3VPmX+B75zvmn+vf5wfkG+2X7cfrr+iH7F/2P/DL94v1c/gv+dv1N/Vv90/w+/D78Pvww/JH9qvzH/Rr/hwBDACgAAQFgAeYAGwCVAL8BegCHAFIBOgPaATkCmQOpBCMFSwUzB4MGdQaFB5EGaAaUCMgHdwdQCLAJyggACdwLQggeCwIKXQh8Ck4HlQl1BjIG4gb9BrYExwZKBHcH0APsBFkFigITBEYCvwH1AVEAegC6/UH+4v2d/CD6Evqm+Yn4X/e89v30q/Qk9AfzCvX99CHy1vU09nLyTvUl9WbzJPT782bzCfQV84HzIvNM9Ar1/vWu9vL2ifjO+c34VvqY+bX6FPvQ+p387fvS+4L8xvyR/U39yf40/kP/Xv93/vH+uv3H/Vv97vy4/DL91f3V/ZH9yf5r/5YBXv+9AEYCywDz/6QB9ABFAb0AUgEDAtwCfQJKBMIDSwU/BmYFrQdpB+MH1gehCJIHkgd6CVIJRAlhCkYKcQxTCsAKVgyICRELKQmjCa8IyAfiBhcG8Qe4Be4FxARpBxIDJAa0A7QDVgMcAdgABAML/qD+nv1b/Yz6zvmn+jj4RPdE90D1PfPg87Tx6vEz9X/ycvL+9cXzjfKQ9KrzdfRL87byB/P788/xFfN08xb0J/aG9lP4l/jp+fn6cfqb+4D7Z/wj/Lj88P1N/f398P1q/vH+hv+HAPP/iQHY/1EA2P81//H+uv3H/ST9nv12/TT+dv2e/b0Aef/mAPQAvf9GArAAGv+lAjcBNgAqAYkB6QLCA28CPAT6BHQFdwdaBgwIKQlrCLwIiAnnCScIiAliC4kKBg3BC2QM0AzQDH8MVgy1DJgLwAp8CokK1gdOB+8GrQeSByMFxQXiBkoEmQP6BGICigKJAcsAGv/x/nb9wfli+dz5sPc09vH1GPUV87byb/BG8DDzFvTm7mTyrfXb8LTxt/Nw8T3zdPMH8+7z+/Oc843yt/NA9WD42vj1+AX6uPyP/DL9j/zi/RsA1v4NADkCXgABAYb/sACWAQQDpQJGAtwCAwLMAV4Avf9r/8n+KP80/gz/x/1b/Uz80/yU/5T/Nf8o/8sA8/8AABsAXgBRAGwA6AGWAfcCtAOJAUgDBwXvBgwI1gc2CXoJYQpGCucJmAt9C6YLPQ0+DhYOxA1lDWcOWQ5MDggOhA/3CxQNzws4Cr4JNgnxB4MGDAgXBksFEwT3AkgDVAIQAocAr////jL9uPzp+Tv61/Yz9SX1WvQh8n7x9e+j74jv/uxS70vzou6K8EvzOvGZ8fjxBPGN8rTxIfLR8o/zJPRY81z1NvdF+Kf6MPzE++L9Jv5e/+X/NgAPAW4BVAKlAqQBpQKKAtwCHwMuBN0DmQNjA9wCEAJsAKIAa/9P/kH+dPzh/I/8tvud/Lb7nv3W/p794v1D/7r9KP9P/sn+KACU/14A5gDLAMAC6QIGBFkFaAbKCNYHegmyCtsKfwwuDLUM0g2pDcYOdg9ND4QP/xAaEUMRlBHXEJMQ1Q/vDo4NPQ0DC6QKXQiFBxcG+gRjAwEB6AHAAioBa/8Y/qz9CPyz+Rv3lfdQ9kvzVfEt8drvv+9b7CDpSuqM6cPpKO6C64Lrz/E58NXszO9w8e7zEfE58LfzQPWS9erxFvRT+G/5Bfpq/gv+KgH0AIcAgASbBIEFgQWPBXcHJAaDBrQDIwW2BEsFqgXFBVoGjANjA7EBbgFgAeL9XP5n/J38Bvvc+Sz5e/hU+Yz6jvtI+jL9dPzQ+rr9j/xb/f/+GP55/zYAsQF7AWMDjQSsBqEI2QlkDHMNTA7vDl0QuxA1ERwSexIQEwQURhO0FHAUcBSMFAQUsxOYE0USxw9pDy8N9AnKCE0GZgXdA9oBlP8o/2r+Z/zE+7X6Hvlf97r1S/Nk8szv8Ow+60npOehR5l3lDOWQ4+/jaOzE6ovoN+9F7/LtwvHP8Rb0w/Lq8Rb0a/Zf99b1Hfjr+o/85f/rA8ACgQWqBUIIzQo2CQIKegkOCUYK4wfzCO8GhQdmBdYH/we4Be4F0AOxAbAAewGs/bb7Svvm90f5DfcZ9gr1rfUz9Rn29fi59G74l/jm99z5jvuA++37dv00/igAbwKKApsE1gcqCvcLdQ4yD6IRzBLAE8MVPBVZFnQW+xbiF+IXxxerF2kYhBhpGAwZ0xbRFSEVAhNREbgOLAuGCGgGtAOJAQz/aP1K+7P5EfnL9/H1WPNy8nzwNe5P7UzrLOht5sjkaONX4QTgLeBS3nveJuQi6q/l+emX8ObuwPDi9Hf1RPfl9m/5c/us/Qn91f3Y/zkC7gVHC3wKcQyrDrcNEBPwD+8OaQ+RD2cOFA20Cw8KawisBhUFFwbfBMIDigLx/gv+uPw7+tf2XPUi87byPPI58B3wKO5F70Xv6vEF8tHyaPQz9Sf2Kviy+BL63/vx/lEAEgNNBsoIwArvDpQRHxRaF/0XoxqkG4scphwtHeocZB35HYwdVh2MHRIdzhw5HKQb5RkZGQkXSBQBElsPcw2UCOwELQMNAKr8Oflf93f1nPPP8Yrwhe2Q6yDpU+eh5STjSuFh3/LcJdtM2nXatdj317XY8tx/6XfkfehI8d7y3vJF+Dv6aP0k/Xf+XgCNBHQFswK2BOcJ2QnbE8sREhRZFmQVDRqDFz0WHhOZFJYShA8gDIkKGAdxAwEB2ADaAYX+7fsS+ub3GfbF873uDu/f6gjr6+mz6HznvOXN53znCOvw7PLtl/AV82TyyvYR+ff5c/sa/x4CCQasBmILgQ3XEGQVhBhKHlkfoiKWI9sktCXRJukklyTnI6MjHSS6INUgLR2bHpodORxFG1EanhfRFcsRaQ8uDCcIPAQcAXf+p/o29zDz2/D/7RntjOkC55TlPuL333nd1du12OfVGNPf0KrRqdAEz8XRRNWn4NflrOP28Fz1WPOA+zT+iQGBBX0CPwa8CEQJOAopCdAMQRDWGF8aXxrhH1YdoCFoIH8doRnmGmYWbBEuDNgIxQXz/wn9p/oG+0j6Kvgi83/y8+6I77Xpbuej5sXigeLP4Nvflt5+4LbhyuU56DTtfPBm85L1pPhn/P/+lgGMAwcFiQpVC98NKBEtFNYY3By7ITwmJCj+KWAsyys2K+Uqayp1KB8lASNbICEeoxp3GIMXJBdLFnQWzhMBEscPcw2yCpIHcQOWARj+Vvqu9tHy9vCu7cbrZerD6QPoROZX4WHfh91m2bTX8dOF0xjTMtLs0JLTaNLt2dvneuYo7mL5RfgU+wEBlgHuBQkGJAZpB6MJZAzKCB4LFA2wEZ8YNhrcHKkeWB5MH94doRnsFd0UTxBhCvsFfgP8/Dv6lfeQ9Cj3ePYV87Txo+9P7fzr6uhE5sfj3+Hf4frhz+Df4Wjj9OZK6mzuP/TZ99D6Tf1eAOsDBwVOB+MHvgnPCyIN4w9sEXAUPxeJG64hPCbqJTQqXyvUKJ4otye0JWAj7R5IHV8aPxfOE6QSvREcEgITOROiEWwRJQ/rDCAM/wc+Bd0DvQAX/RL6eve59BPy9e8p7/LtCuw76aHlgeLn3qDcmtjZ1eXU/9Mz0+LSudJD1KDcl+fZ5m/wA/no+HT8ov/MASMFfQJ0BRgHJgfZCfsFeglHC7oP4BYkF24bKht/HWUe3ByqFqoWfBPyEL4JMgZGAiH7b/n+9br1UPYz9e7zgfMQ8EbwT+106y3pX+YP56HlhuXi47nj9Oaa6fDsZPJc9Yz61f1sAAYEFQUbCR0Kegn3CzsMcw2cDWcOURHOEyQXmh2iIkQjICb7J+0ntCUFJm8khyLSHmwaTRcuFQ4SuA78DnYPXhFDEdgRDhJPEBkQxg7eDMAKlAgkBugB1f2n+r73hPUw81XxRvAc7+7rv+fW5HLh2N0I2lbYYdZf1VzT09Fc09HQmdew5hjkuuxf9w/4jvuG/30CPgUTBFwH4gY1CG4KWQXMCSwLnQ6cFj0W5hr0Gs4cPB4UHp8YaBeoFVQTRwtNBvUB6/o5+UD1MfSQ9Jzz+PEF8svuDu+g7Qrs+emY6BHosOa85WvlnuO+5iLqQe0h8uP1f/oM/1IBFQWgB5gLFA3rDLcNxA0+DqkN+Qy6Dx4TzhOfGCAdTyFtI0glcycwJ3Im+CX1I64hpBvHFyEVDhLwD8QNxA2QDkAPXRBgEigR8hCHEbARQRCoDG4KgwYEA/D9O/o4+NT0LvId8BzvMuzD6Q7mu+Sn4JXdCttk2BHX8dPi0sfS7NA/0ozgIuJF55fwnvRs91z+ywBNBhoIUAhdCKQK7Q2UCDoLiwvtDRATBhUKGF0ZsBrrHTEffx2jGicZ7hasD4kKMAXk/qn7X/dm8z3zIfJt70PuGe3y7RruGu7+7Ajr+emn6eroz+iI5onnp+l27Jfw7vNR96r8vQAhBGsISg26D+QQXhFDETUR2BHLETURJhDYEacU7hbWGCMfTyEBI9EmtiZkJsMmVCQmIUgdhhmoFWAS8A/eDJgLOwxxDPwOWw81EcwSYBJhE4gSXRCODdsK+wVFAZH9s/lc9WTyDu9n63/py+aD42XhHN4y2xTZ6teI1XfTJ9TW07XPidaq4gbhBuoT8q31pPjW/jAFkgc2CR4LjAyEDwsQ0g2CDu8OlBHAEyIWhBgzGHoa+R10H0QakxklGN0UJQ98Ci4Eav5I+rr1tPGx7xruBupK6vfo6+nt6mfrgOqa6cPpqeqQ6/npnOq36oTsv+8F8q31O/pN/XsBMgYDC00PlBFvE84TIRUVFrQUwhQeE1ERihMEFN4V4BZ9HJ0fnR/lIkYk5yNGJDQhFyDBHK0YLRQ1EfwO9wsACcwJ9AnoClYMgg6FEA0RiBIeE1ERkQ+ODQ8KFwbMAfz8v/gz9Tnw7erD6QDmnOKY32zdFtp/2G7WD9Yp1crUUNT80RHXqOFI4DjnAvAh8v30Tf3AAqcDFwbAClAI+w3zEbcNdg95EWwRHxQuFSQXchWfGIscAhtBGMUWIRUQExYO9AlKBP/+I/zl9lfyRvDH7CDpi+jb57Lny+b36Jfnvuaa6afp+uo+6xbr4evy7afxWPMM9kj6+vte/zAFGAdxDIQPJhA3Er8SIRX4FN0UKBHYESYQAhN7Eh4TtBQMGW4bfRzSHvwfrCCRIGUeixwdGwoYzhPXEBQN9wt6CfMIrwi+CYwM3w1bD8sRvRFIFBAT1xDEDZgLGActA9P8svic87vt6ui85XTiN94l243Y2dVe1KDTQ9Rm0XTRL9CKzurXe95P3Cflduz860vzffmg/kMAmAL9Bq8INBDjD+EONRFdEMsRzxRyFfoVmxUnGR4ciBoKGAcWthWiES4MegkHBXn/gvzj9RHxN++Y6CnmGOSc4hXix+Nc5DLjuePI5FDlOehi6L7mTOtq7RzvqPKe9Gz39fgJ/doBSwWJCowMkA4qEm8TtBSAFZgTiBIOEogSHxRhE2ETcBTiFykaOBuYHJseFB6AHkgdERwCG+wVVBNAD3EMbgr/B6wGWgbUBjYJiQp/DHMNFg7/EEAPTA7qCw8KuAX0AGX7yvYd8IDqROZX4ebdcNdE1VrS+M8Qzs7Ows+1z0jPY8+A0K7ced1v3/foDe4B75P2IPq6/Wv/lQBlBP0G3w3PC38MdQ4lD0US3RRVFHAUgBVpGKQbChgTFTkT2BEGDWsI3QOG/1f7hvZj8fLtt+ob5u/jtOBx4AbhLuE+4o3h0eH940LlAOYp5m7nBuqg7fPuPPK59AH43Pms/egBjwUOCYsL4Q7wD20SEhQeE0MR5BDyEFISHBJsEZQRdBZcGBkZyxqyGx4c9xzBHAMcbBpoF0gUNRG3DdkJ8QcXBpsEjQRlBLkGJwgbCYkK6wwIDmUNjg2oDPQJ4gZ7Abb7Ufej7zvpoOT13gfZNdRm0dzOX8wozAHNls0ezhTQjM8A1Ujg/9xQ5U/tQOw68db1A/k7+nP7bADaAf0GfQuyCowMQA/wD/YTExVLFpwWGBg4GwAaBxYqEv8Qcw2vCO4FhwAI/PX4n/Ud8Lvtw+mG5WnkxeJ04gfiJOMH4i3gxOEV4j/jM+Qn5QDm6+n+7G3vcvIZ9r73FPtRAB4CkgcRC38MFw9pDxwS2BFDEWoQug+FEEUSKhLaElUU0xZsGnoafBvOHKcd+h5/HTkcABoWF7MT/g/DDHwK8QcXBjIGgQULB4YIKQl8CqYLcw1nDmcOqAwDC5QIZQRP/i36t/N47aTnWeIN3VbYoNPf0M3NAMxry0PMA87OzuvP39BC3APfE+HB6G3vDe7g81H3LfpN/Sb+AwLdA3kI8wgbCesMnQ4LEIoTjRV0Fv0XRRt9HK8ZdBZwFJgTJQ8PChUFzAGP/Cr4ZvMr8Kzsv+cb5p7j4uMy4zPknuPg4sXiCuQn5Q7mUea+5gbq7us17ufv+vJC9qP3Svsa/4wDoAd8Ci8NQA+wEZYSRhNgEjkTEBMrE5gTcBRjFIMXKRopGmAbphzfHmcf4R9ZH38dfBtOGI0ViBKdDjoLhggzB+AFnQUyBp4GoAfKCMAK3gyODYENPQ3qCwAJxAQNACH70vMZ7Xzn3+FA2wLWCdLazTTLM8rIyjbMYs6p0FnRZNgH4kviZOmK8C3x/fQ4+LX6rP3W/uYAzgIjBa0H4gYpCXEMjg3JEDoUFRaEGFEaSB3OHNYYuRc9FnwT/g+VCXQFDwFK+9f2wPCv7hTqD+eh5RrlaeQY5KHlhOTj5Cfl5+Zi6M/oSekG6v7sXO0N7h3wIvNp9Wz3CPy9/5sEQQf2CgYNaQ83EnwTgBXqFJsVmxWBFuwV3hV1F0IZ5hrZGoscPB4lIPwfuB/EHusdpBuvGccXpRO7EI4NzQoOCawGTQaqBaoF/QZOB9kJVQvbCugKAwvzCGkHEgPY/875gfOF7efmwuDE2fHTH89dy0zJ+ccWyV3Lbs0Sz7nSKt4W4yrnVPB39aP3c/tq/mABywBiAjoDbwLFBRcGpwPjBzYJUwoxDgESgBWqFh4cZR6YHJcb5hpQGd4VahCkCqwG8//5+mj0e++46zbmaeS44tTjnOLU4/7k5eW+5pjoxutN7EDsau037wLwVPCz8H7xWPNa9A33i/lP/swBSgSUCBIMnQ69EZsVMBb7Fv4YkxnXGUUblRodG3Edzhw5HAUdth62HgYe3x5/HSwcvxuhGdMWLhUOEkEQdQ4FDKQK8wg2CfEHdwdQCBsJNgm8CPEHQgiDBi0D2AAI/Cj3tPFb7EXnOuCr2gLWMNE3zaHLrcpPy7DMOc61z5TUH+Ds4bLntPHg8+b3dv2/AXIEmwSFB0EHQQeyCrwIQQcuDAAJYgvTDmoQwBNvEykayhm8GVEa1xknGVoXyxEjDnwKHwMbAGz3TPST7QPo5+bg4nXj+ODs4bji7uLI5L/n3+po7MntAe8V8+DzP/SS9a72h/dE98L6gPtB/qIA6QLFBcoIiwuCDvMR6RP6FTMYAhvcHIwdgyANIuUihyJEIzcj5SJDIv8hFyDQHYscbBrIGI0VvxLyELoPqw5JDBIM3AsDC80KwAqyCvYKOArMCWsICwc8BA8BQP1u+CLzbO6n6eDivd1k2IbU3c/azSjMk8uVzHvNR84w0ePbOuBO5K7txfOQ9ID7pAGnA8UFoQjMCQ4JfwyMDPEHZAxwCyoKgQ0mEEMRsRLHF2kYaxlCGVMbNhopGgkXexLjD6MJ7gXW/n35nPPH7M/o8+W54xPhfuA53/jg6+Dv47LnZOm46//tIfKD9JL1DffL92/5LfrQ+pv78f55/+YAmAIVBQsH2QnSDWoQEBPeFScZ9huAHnchsSM8JqgmIidzJ/snByeZJYgjQSHtHgMcehpoFy0UsBFdECUPgQ3QDJoMSQyoDJoMZAzrDBIMOguVCYYIFwZiAuT+BvvI9WHwaOyw5sLg49sT2DXUV9CYzr/NpM1xz4DQCNFf1ZbeY+Cw5hzv+vJA9cT7RQEDAvsFvAjzCKQKcw1/DB0K0w5VC4wMkA5qELsQpBLUFwkXaRhcGCcZeBkMGY8W2xNSEs8LAAncAnf+sPcu8kPup+my5xjkgeLR4Urh6+BZ4qHly+an6TLs9e9X8j/0hvZu+Ej6+fpM/Mf9yv/LANoBjAO2BGgGGgh9C/sNNBBVFHcYsxzuH7EjFiiTKl8r3C0SLtAuLS6JLIQpZCaUIqkeDxvvF6UTTxD8DvkMOgsRC80KiQpuCn0LwQtWDGQMAws2CbsHtAOU/6n7KPeK8MbrUeb337fZetXR0CrNycuEyrrKX8xvzi3PJ9Tz3d3g9ucf8TT2v/jK/8QETQY4CrUMZAxzDXYPgQ1hCj4ORwthCowMxA2dDhkQBhWbFYEWDBmTGUQashtCGWYWZBVPEC4MuQYqAS/7JPR777fq5+Yk46fgA99g3ireOd/s4cjkHecj6wHvE/IK9Tb3BfpZ/O78Jv5r/4cAHAGkAaQBmAKMA98ExwawCS4MGRCZFOMYOx2HIi4mNCpHLewvjzAzMk8ygjBULbwqzyW7IdAddxjpE64QZQ2kCjYJkgfiBhgHuweUCDYJbgroCqQKiAlCCI8FEALV/R75t/PJ7QPowuDU2kTVFNBdyyTJw8fPxjDIQMoMy4zPjtnY3VzkbO6Q9PT35f8wBaAH9grfDfsN3w3/ED4OHgtKDW4KhggbCTgKRgp/DIUQohFgErYV4BbWGNkaoRmSGKsX+BSHEVYMGAfLAMH5+/OU7prp1uTd4FLeatyr2uHaatzn3oDhhuV/6ZPtVfH99B34V/v8/Gr+UQCxAYoCfQIDAisC9QHoAVYDPARoBr4JZQ1FEqoWixziILQlripiLUswGzQrNbE0UDOdMFMs+yeII8IdQRjbE+EOAwsMCPoE6QKlAm8CEgMTBLgF7wbWB9YHoAf7BToDNgD8/If3BfJA7PHkN97B12bRT8vRx1PFQ8NDw77EvsQwyILR9NWH3W3mlO6o8j78EgNBB4sLQRANEYcR+BR7EhcPJhA9DW4KXwltCXcHoQhiC7QLqAxbD3kR2xMkF2gX1BerFz8XZBUqEkwOawg5AuH88fUf8S/q/uTA37zcf9hw1+jWR9fD2E/cOd+Q4/bnhOxh8Mj12vi2+wz/YgJxA8QEmwTRBEoEPARKBGUEFQXHBg4JSQxdEMIU1hjeHSkjwyZ6KzAwGjNfNDg1RDRNMfguKCvCJdUgvxvDFbsQVgxpB7QDKgFr/8f9Jv5B/ij/ov8AADYAAACg/nb9+frm96rzlu+M6STjQ93N1hTQT8t/x5TDQMFMwPm+PsCoxzTLgtEj2oDhpOfA8BL6QwB1BkoNyRArE60YCRfsFZwWHhPkEIENnA3nCYYIvgmSB9YHXQhtCdwLdQ5bD70RARI6FM4TDhIcEsMMbQkwBfP/gPt19L3uHugJ4wHegdnN1mvUDNRr1NnVjdiR21TfGOQt6aDtw/Ll9nT8yv/AAqkETQagB4UHeQjzCPMIRAlTCmILgQ3VD6QSwxXlGacdQSGoJhkqiSzdLmYwPjBLMHEusCvvKGEk7h9fGt4V4w/oCpEG3AJ5/0D9SvuY+Sz5Rfgq+PT3Ufe89vH11PRk8rHvF+yk5z/jpN4H2V7UctAozJzIVcZQw3bBhcL4xsXI6c5r1GfaH+Ae6GHw1/as/UsFNgnhDnAUjBTuFu4WjxZyFaQS9hMXD8YO+w1VC5UJ5Qj/B/MIKgoqCvYKpApKDYwMZAyoDLwIeQjRBKUChf7p+Z/12u/G69flZeHY3Z3aE9gR10bWiNVV16jY8Nva3gnjo+YI62PxnvT1+I/8r/+zAgcFoQiwCbQLZQ0KD9cQiBIfFIEWJxkCG+sdTSDnIyAmCSifKTQqGys2K6EqGCnsJnwkdyHCHXgZwxVDEdINvgkyBpgCAAD8/Fb6vvfW9arzmfHn7xru0+s76VHmTePO313cqNgA1cXREs+8y57JjccrxUTEVca3yPDK6c4a1HLYld2g5ErqK/BR93b9KgHKCNAM0w7LEc4TtBTpE3QWwhTbEx8UEBP/EKwPuA61DJwNmgymC80KVQvNClIJlQkkBnQFfgP0AMn+3/t7+KrzH/G67B7ou+Ts4YneJtwK243Y99c72DvYZtmE20Xe29+E5NvnkOvm7knyk/aL+TT+5gCABMgHpApMDk8Q9hM9Fl0Z6BsxH8cgliPPJeAnCimrKK4qTimEKe8oEyYfJXkiqx9wHGsZqBVtEiUPtQzYCOAFYwPK//39tfp7+P71S/Pp8Cjuguuz6ELlZuKk3hfbINjx0z7Rs87yywrKcscsxszEi8YWyePK6c6R0m7Wxtrd4KPmrOzd8VT5j/zpAjUIHQojDv4PKhJUE+kTZBVVFLQUzxTMEv8QrhBMDnYPZw5YDX8MEQtwC20J8wiSB3QFSgR9AqIAav6A+yr4d/V+8UPuqer2513lMOK04Bze/tuE2z7a/Npb2+Tc2N0f4D/jXeXq6FnrHO9y8lD2Lfqe/egBdAVECUkMeBA5E3UXlRqaHZ8gryIgJpwn4Sg0KicqQytdKjQqdSgwJzol5SIyIC0dRBp1FzwV8xF2Dy4MGwmRBkgDYAHw/S/7U/gl9cPyUu+f7PfovOV04hDfkdvP1wDVndESz1HM4cmox1XGK8XPxjDIQMrZzNHQa9SN2DfeQeQg6TfvyPVv+SgAcgS7B3ALTA6HEVISpxTsFS4VjxaPFiEV2xMSFBwSlhJ5EeQQgg4WDmcOcAt9C18J4wfUBiMFfgPYALv+tvs5+VD2PfMd8Fzt+uq/5+Xlj+Lr4IrfHN6V3f/csN153VTf+OBZ4sjkOOdK6kHtcPEK9WD4Tf0BASMFDgm3DeYRMBZ6Gvkd4iArJIEnJSmVK24sVC0tLootby1sKycqgyguJogj4iAvHrIbGRlLFqUTGRDfDRELNQi4BW8C8/+P/Ej6NvcJ9PbwDe5z6onnkuRx4FHd7dlu1qDTgNBUzobLCspLyFjIZ8kYynrMwc6D0lLVCNql34Tk+enA8IP0tfrz/9ADUAimC7oPyxHbE/sWCReEGNcZrRjUF/0XgRaPFmQVBhUQE14R8xH8DpAO0AxHC3wKygigBzAFtAO/AVD/Mv3d+g/4rfX78+nwHO/86+vpOejz5TXlFuOQ4wfiFeIW4yTjkuS85fbnFOr+7MDwdPPL9/r7KADQA1IJqQ03EloXYBurH/MicyfVKb8sBi8wMD8xxzHVMT4wLy+mLXorCimaJjcj4iBlHiobaRgGFYgSWw/eDAIKGAe2BBACyv/8/HH6bPdO9WTylu+R7Dvp5eXR4SvfTtvq1/PUdNEfzyjMNMtry8jKvcx7zRTQP9Jh1pDawN/U45zqAe9a9Ab7rv7QAycIcQzwD5YSSxarF4YZshsRHAIbERwdG1EaiBpQGf0XchVZFnwTiBIoEboPPg7DDBIMbQmvCE0GPgUEA5YBa/+4/Ez8VPnm92n1+vL28Njuye0W69Lqs+ge6G7nYef05lPnfeiM6Wfrk+0r8N7y8vZx+hj+HwPWByAMNREVFrAaqR7MI1gnySrcLZ0w8DHYMyk0ADQnMyYyuDDpLdkrqyjPJcoiuB9HHOMY7BWkEtUPSg3bCl0I7gVyBLEBDQB2/cT7VPnK9iT02/DW7UrqOOes4x/grtxm2TjWM9Mw0ZvQH8+az8LP7NAJ0gDV6tf+21TfyOQg6Q3uMfQq+CT9UgEXBswJcw01EXAUgRaTGR0bUxuLHKYcfRxIHdobiRsZGWsZxxcHFrQUpBKHEboPCg87DFULNglCCE0G7ARxA4kBywAa/5H9MPwS+r/4DfcZ9kz0B/O08bPwbe/Y7tbtT+1P7VztGu7z7pfwBfL99If3wvri/fUB+wUqChcPORPUF3AckSCyJBYo2SsSLrgw/TEMM/8yJzNPMjAwSC5fK3Uo6SS7IbUdURqqFnwTrhDEDYsL5QgYBz4FcQPMAeX/C/7t+9z5APda9GPxbO4x6xHo/uRy4dredttY2ZrYpdaJ1qPVldWj1dvWf9j82hvd3eAm5DjnQOwO77fzevfE+9j/VgMYBxELcw0aEYoTExUJF04YXRkdG3oaiRsNGsoZrxnUF00XPBVIFDcSKBEXD8QNcAuXCqEIxwadBd0DpQK/AVEA//6e/Vn8jvtW+ov5U/iV97z2GfYY9Wj0+/Oc84/znPN084P07/Qn9pX3LPmA+039QwAEA00GvgkUDYUQBBTvFyobxB7xIdskSyclKeUqXytgLA8sNivjKaoniyXKIkAgIB0AGloXjBRFEgsQFg6LC9kJ8QcJBhMEigJeALr9gPtT+Hf1BfJF77jrs+ih5eDiH+DY3TbdCtvh2u3ZStkv2Y7ZTNr+22zdpd/E4QrkpOfe6U/tl/CB89f2Vvpo/b0AjAPHBkQJRwtzDWkP1xBhE4oTLhVJFVcVBxY8FZsVEhT2E5YS2BFBEDIPgQ07DOgKNgm7B2gG7AQGBJgCYAHY/4X+4v24/BX8SvtW+rP5VPna+G74HfhF+Cr4l/iy+FT59/kh+zD8F/3//jYAVAI8BJ4GrwgeC5wNCxCkEvgUWheGGaQbLR1KHkwfqx/hH7gf0h5/HR4cehr+GPsWZBVvE4cR/g/SDX8MUwrYCAsHFQUSA8sAkv4V/LP5vPbu8+nwDe5n68/oUea75AnjcuHP4FTf595S3pbeK98S4BPhj+IK5ADmHujr6Xbsr+4E8fvz/vWX+BT7g/3K/24BpwNmBbkGlAgqCvYKVgxWDKkN7Q1MDmcO+w1MDggOnA35DFYMLAsDCwIK2Aj/B+8GTQYHBS4EEgOJAQ8BAABQ/zT+/f3T/HT83/v5+pr6SPot+gX6IPpx+rX66/oI/Fn8kf2g/r3/iQHpAsQEdQY1CEYKEgzfDeMPlBErEy4VIhZaFwoYThi7GDMYMxgJFz0WchUtFB4T2BFqEHYPIw49DcELHQq8CMcGPgVWA5YBef92/S/7l/gn9rfzOvHL7oTsc+pJ6W7nbebx5O/jMuPu4uDiTePi4/Hk1+VF5xLpFOoy7OTtAvCZ8T/04/Ud+Dv6FfzH/V7/5gArAlYDZgXgBbkGuwfxB9gIygiICQ4JegmVCYgJ8wgACUII/we7BzMHWgYJBo8FBwWABMIDLQNUAkYCYAHmAJUAGwCi/1D/u/6F/v39x/26/YP9aP1o/Z79x/1c/nf+5P5Q/14AbgErAmMDjQSqBWkHrwgCCn0LFA11DuMP/xABEtoSihMEFDoU6RP2E28T2hJSEjURkxCRD9MOxA2oDLQLYQpECf8HPwbRBC0DlgHK//393/t9+VH3M/XR8orwXu7H7Ezrf+nq6FPnX+Z45Wvl/uSG5fPlo+Zh56bo6+nf6p/sNe71793x7vNA9VH3LPkU+wj88P0a/0MA2gFWA6cD3wQwBSQGPwaRBjMH4gagB3cHhQdBBzMHuQZ1Bj8G+wUVBSMF7ARXBN0DYwOlAgMCKwKJARwBvQCHAEMAr/9r///+yf7W/pL+XP5c/k/+T/6g/hr/8f55/+X/hwBFAWICOgMhBEsFrAaFBzYJiQq0C1gNIw6ED4UQsBF7EswSbxOYE1QTRhPaEmASohHXEBkQFw91DoENfwwsC/QJhggLB48FLgRUAssA5P7G/Kf6bvgn9u7z3fGW7zXuhOwI697pHuhF5zbmyuW85eXliOYC54nnIOm16e3qduwo7szvwvHg82n1RPdU+d36FfzV/VD/QwD1AUgDmQObBCMF0wXFBWgG4gZaBv0G7wasBiQGTQbgBYEFWQUwBYAEZQRKBMIDVgMSA6UCEAL1Ab8BpAF7ARwBAQGVABsADQCU/9j/hv95/1D/Nf9Q/zX/DP9D/5T/5f9eAAEBlgErAvcC6wPfBPsFaQeUCA8KpguaDO0NJQ9dEIcRUhJGE6UT9hM6FPYTmBM5E5YS5hH/EE8QWw9ZDkoNLgz2CogJUAjiBnQF+AP1ATYAT/4+/C369PfW9cXzfvFt717uMuzf6qfpLOgq51/m8+XK5bzleuaw5h3nweg76anqMuwa7nvvmfGq81z11/Ys+bX67fv9/Wv/XgADAlYD6wPRBHQFPwY/Bu8GGAe5Bk4HMweeBiQGCQaqBUsF0QSpBN0DtANIA7MCRgL1AW4BHAEPAb0AXgCHADYAAACi/73/ov+U/73/lP+9/73/ov+v/xsAyv8NAF4AywDYAKQB6AGlAkgDVwQwBcUFTgdrCHoJHgtJDHMNqw7wDygR5hErE5gTzhNVFC0U6ROzEzkTexKUEaAQxw+rDu0NjAweC8wJUAjHBnQF0APaAdj/8P3S+7P5X/fv9Lbyl/Dz7kHtTOtK6pjoYedE5q/lDOUa5WvlKebl5Q/nOejc6MTqTewN7rHv6vHS8+P15vcg+pv7JP1e/70AzAHQA6kEqgV1BjMHyAfIB7wIawihCNgIawj/B60HaQfiBloG+wUwBbYELgTrAy0DigIrApYBbgEBAcsAegCiAFEADQA2AMr/ov8bACgAAAAbAF4AQwBDAKIAywCiAG4BiQH1AYoCLQPCA0oESwUyBscGJwhtCXwKBQxKDWcOnw/yEA4S5xLpE7QU6hSAFXIVZBUTFacU6RMeExwSKBHwD8YOnA0SDIkKGwmSB+AFPARUAl4Ad/4+/Pf5sPcY9d7ypfBF71ztPuuO6lXoOOeI5vPlQuV45QDmeubL5izoEukU6iXsDe6j74vx+/PI9fT3IPo+/Lr9r/+/AfcCjQS5BgsHJwgbCb4JRgpuCiwLzQoRCywLiQoCCucJKQmvCP8HkgesBjIG7gUVBYAE0ANxA7MCwAIDAqQB2gGJAWABHAHLAAEBogDYAKIAsADLAMsARQEcAVIBsQG/AfUBzgItA4wDEwQVBUsFWgZpB10IUgn2CjsMIg3GDk8QURGWEh8ULhX6FeAWxxfHF1wYrRgKGGgXTRd0FhMVLRQrE2wRNBDGDusMVQv0CVAIFwaNBIoCQwBP/j78mPkA99T0V/IQ8Obux+wj67XpVegd50TmKebX5QDmy+Yd5/bnSell6uHrye0C8JnxJPRr9pf43fqR/Wv/HAF+A3QF4gbzCHwKVQtxDIENTA4+DjIPWw9bD00PWw+QDu0NnA0GDfcLYguyCpUJDglQCHcHdQYJBj4FqQQ8BNADLQMEA+kCpQJGAmICAwIDAlQCOQJUAqUCwAISAxIDpwPQA/gDxAQjBdMFaAYzB/8HlAi+CcAK6gsGDasO1Q8aEbESwBM8Fe4WChhCGeUZKht8G7IbRxwRHHwbDxtfGjUZ/Rf7FkkVihMBEjQQTA6MDOgKygisBrYEfQLl/+L9jvsR+UL2JPSn8RDwbO4y7AjrSekR6B3nbeZf5jbm9Oay5+jnw+nf6k3sXu6z8Kjy4vSV9y36Z/xr/6QBtAPTBVAIKgrPCyMO4Q5PEHkRYBLMEhATzhOlE2ETwBOxEgESvRHJEBkQCg9MDusMEgyLC24KNgmvCKAHxwYkBsUF+gSbBLYE3QOnA7QDOgNIA4wDwgNWA8IDPAQTBIAEMAUjBY8FTQYmB2kHlAhSCdkJ6AoSDEoN7Q3VD0MRYBIEFJsVnBZcGOUZUxsRHEgdSh5zHiMfIx/SHlgepx2mHFMbDRpBGJwWzxTaErsQnQ6aDKQKQgh1BiEEAwKi/3b93fpF+Nb1PfPb8Dfvau1n60rqR+gq51/m8+WU5Q7m5+ak533oIurT61zt2u8T8pD08vYF+mf8Q/8QAlcEkQbzCCwLIg0lDzURARJvE6cULhUVFuwVnBZmFksWZhYuFX4UzhOWEvMRuxCsD0wOWA2oDB4LUwoACScIMwd1BqoF3wT6BBME3QNjA7MCwAKlAsACwALAAlYDBANjA1cEVwTsBKoFgwbiBgwI8wj0CegKSQw9DUwOGRDLEQITIRWcFqsXkxnmGnAcjB3EHsYf/B+sIPAgJSDhHwgfmh05HKMayBgwFpkUDhJ2DxQNHgtdCAkGPASxAWv/W/0h+5f4Xfbu87TxAe//7Qrsf+nq6CrnhuXW5JLkaeSg5LzlAudu59DpTOvH7CnvLvKQ9KH2SPq4/Br/VALRBNQGDgm0C9IN7w4cEvUS2xMuFTAWjxaBFloXCReqFsUW7BWMFC0U5xK9EWoQxw8IDtAM3AuJCg4JrQe5BlkFVwRKBDoDVAJvAg8BAQEbAFEAAAANAIcAhwBsACoBUgGxAW8COgPrA3IE+wW5BkIIbQnNCuoLWA1ND64QiBLCFFkW/RflGQIb3BynHZ0f7h/iIEEhCyGsICUgCB+MHXwb5RlaF6cURRJpD6gMRAkYB9ADiQEo/wn96/ra+JP2ufS08drvhe0x6+vpR+iI5tflJuTT4vrhWeIw4gnj/eMO5qPmLekW66zsHO9y8qv0RPeM+qz9GwAtAxcG1gf0CbUM0w7HD6QSbxMfFDwV+hV0FtEVjxZZFrYVgBXdFOcSRRINEZ8PIw4GDXALzAm8CFwHnQX4A2MDiQGVADYA1v7W/hj+dv3u/D78TPxZ/CP8Cf2C/Gj9uv0m/sn+ov9eABwBswKnAzAFuQZrCKMJYgsiDUAPuxArE7QUnBatGPIZpBvOHPkdxB5nH/wfnR/fHqkeLR2JG68ZkBfPFFISxw/QDNkJrAaZAw0AW/3C+kX41vUJ9HDxlu+77YLrVulF54blXORo49/hgOES4H3fVN+K39vfIeGc4lzk5eXB6MTqkewC8NHyhPVT+Pr7hf6kAakEQQe8CDoLZQ0lD+QQAhN8EwQUZBUGFSEVjBTdFMATYRPnEpQRkQ8lDyINiwsCCnkIngYHBWUEOQLYAEP/GP7G/Lb7PPtW+qb5i/no+Dj4Kvij91P49Pe/+BH5fflW+hT7I/wX/Sb+r/8qAfcC3wSRBhsJwAoiDcYOKBE5E1cVkBdQGeYaYhx/HXMecx4+H7YePB6aHR4cXxolGN4VYRMZEMQNYQoYBwYEywCD/c755fbu8/bwee7T6y3pD+fj5Anjp+BU3/PdXt0m3KDcadtA25/beNzy3JbeBOA+4tTj2eZx6SProu6n8ZD0Nvch+7r9ywByBE4HKQkeC98NWw/XEPUS2xPpE5sVPBVyFS0USBRvEyoSohFBEFkOBg3BC18Jkge4BcID9QGwALv+JP0G+0j6ifh49l32aPRM9KrzWPN/8lfyBfKo8nLydPOq81r0/vUN9274ffmb++78Nf+xAfgDPwYbCX0LMQ5qEDkTExWrFw0aUxtWHfkdWR+rH48fdB9zHkgd9hvXGccXLhUcElsP3At5CMQEewGe/d36RPfu86XwoO3S6h7oa+UJ46fgHN7/3CPaB9nP1+rX29Z914vXwNZ911jZWtpC3JbeZeEJ41HmL+qC60Xv+vJr9s34/PxsAMACrAZGCtwLZQ2FEDcSKxMuFUsWthXFFhYXIhb4FH4UihOwEa4Q4Q73C1MK2Aj7BacDbgHx/oL8SvtH+df2QPUk9BPyl/A58K/uKO5Q7rvtC+1c7UHt/+1Q7pbvEPA68fryufR49r/4wvr8/PP/igJmBXkIzwuCDpQRfhRNF0IZERzeHWcf4iCuIdYhySFqIbgfPB5HHMoZ7hb2E8kQ6wyjCe4FvwEY/n/6APeq887wJu3r6W7noOTf4VTfNt2d2qjY9ta91OLSatMz07jR5NPw0rnSodQs1y7YndoB3iHhquL255Dr/uz48UT3ffl0/FQC0QStB1YMCxBBEFISjRVZFqoWyhkZGbkXeBkYGOAWYxSnFLARkQ/hDs8L1gcLB5sEAQGg/ln8R/ny9gz2dPM68Yjvy+5N7Ezr+upx6SDpten36MHomulx6d/qZ+sm7YXtzO888mj0vPbc+Vn8Q//3Ak0GegmODWwRVRROGOYaIR5AIAEjlyS0JcMm0SYFJpklsSNPISMfpBuEGEgUrhBkDAwIZQQbAKn7Afha9MDwau3S6kXnd+Q+4orfXt3G2t7YONZQ1OLSctAfz6fPVs+KzsTQBtCA0OLSAtb21qvalt5L4njlI+uj78/x5vdN/TYALgTMCXEMTxDqFMcX/RdRGnAcmBz3HKke3BxTG0cc5RlaF34UVBN2D3MNLAt3B90DHgLK/477ffnl9o/zPPLA8K/ukewx65zqLOiy5+fmeOW85VHma+WG5bDm5+Zw6BTqZ+sZ7efvS/P+9ab5Tf0BAZsEKgrSDQESCRcCGyMf2CJJJnUo8ipULfctIC5jLiwtDSuSKX8m5CHEHg0achVBEMEL/Qb1Abv+s/mf9d3x5u4W6+roUeYy4/jg9d7/3ODZINi+1dTSPtEEz3rM/soNzKHLksoDzl/Mzc0V0b3U9tbV27bhvOW36gXyRPe1+lQCawjcC8kQqhaTGVYduyFtIxwjVCRIJWEkDiP1I6sffx0tHZIYMBaUERkQHguvCOIGvwFr/1v9c/tE95/1IvMr8EXvu+3h6xTqpuj25/7k/uQy48ThPuIH4nLhV+GB4u7iyOSw5hLpqeoB70z0U/h2/S0D/wcvDfYTrxk8HsAk/iktLtUxUzW1N+w3Tjp1OX836DVDMyMw9CucJ/8hYhyDFxwStQygB8IDGv/E+5f4nvQh8hzvQe3S6pjoeuZO5BXimN/X3GbZAtYX0sLPKMxzyBHGGsNfxBzE5MKLxjrGWslHzrvTE9gE4NnmN+/+9TT+kQayCpgTlRpKHmsiZid3KSosBC5HLaIr7ygkKOolxyDVIKMa7xfeFYcRJQ/nCbAJ4AUuBEYC5f80/j78j/xF+Mr2WvQ68ZfwGe0j6yzoNeVO5DrgYN7I22faMdqO2XPZFtoL3IfdIuIz5NvnJezC8R34d/4+BUkM9RLlGRkh+CX0K+IxBDatOg89Hz9lQHJAqECWPdU6fzeUMzwvhyvdJdUgRxwkF8wSxA1hCuIG3QMeAgz/qvyn+gP5QvZM9M7wQe3E6svmueOk3jHaN9VWz2vLEcb9wae+y7vUuJy3AbyvusbALMYxyXHPLth+4CzoS/NZ/I0EtAuPFh0bPh8UJ4Qpdym/LCwtbCvXKnor0SZ7I0AgqR6GGUEYrRg1EfYT8hAoEXUOCA4jDrAJRwtrCJ0FHwMqAQv+OPi69aLuw+k25qfgAd7318DWx9LE0BXRVs8w0cfSYdbe2HveTeM76fXv1vWb++YATgf5DG0ShBj3HJQitydCKt0uPzE1M0Y1IjjDN505QDqROgo6xDg9OHkzQTJZMBwskCiZJRkhfx1rGdEVyRBxDAAJBwUAAEH+9/lr9j/0b/CR7APoDOWZ4Dbd+dht1UrQbMzhyW/F/8KCwPe9KrwAu2fAhcL2xenOF9JH1+nfBek17un5NgBQCIIOxRY8HrYeBSaqJ44ntye5KEsn3SUxKL4jlCL6HsId6hz9F5cbjBRJFeoUpRP2E10QNRH2CjoLPwboAdb+v/h698zv/Otf5pjfvd0f11LVndH3zsLPs87U0gvTpte42sDfCuSM6W/wg/QX/RAC4gZiC2kPiBLsFScZehp9HCYhbSO3J64q3C1lL9Yy9DTBNhc6CztiPtg8LT9sPLo6FDjYM5ou7ygOI84cJRhSEgYN7wbaAeL9YPj+9UvzzO8C8BntXO1z6sPpD+dc5ErhrtzD2E3SStBbyiDH8cLrvtm7TLgPvFa+WL/FyFPNMtJe3ejnve4G+/gDtAvbE24bBCXbJAEs3S5FLFErDStmJ+cjlyRKHh4c4he3FmYWGhFmFuEOJhB5Ea4QNxLkEBwSxA2pDfQJVwQQAn35o/dB7YzpZuLU2uzYj9EEzyfLkMlMycjKjM9Z0Y3YsN0M5bjr+vIv+/P/8QcUDa4Q+BQlGKEZKhvOHA8b2RrOHO0enR9SI5om+yeVKwkxDDMFN4Q6HD3mPB8/fj9DPLo6BTfFMBgphyJTGx4TnA2RBkP/tfon9tHyRe/L7nTr3+q36gjr3+o96iLqYed45XLhyNsf13TRD81Xx2rCVr7xud62DbtvvVa+qsgczTPT6d9066rz2AB8Cm8TGxp7I64q/imaLp0wDSuEKY4nGiJYHs4cMBYQEyUPuA7vDsAK1xCJCj0NGRB4EEUSbBHXEN4MwQsmB1IB/Pyc823vreTb3xTZ7NAh0BbJc8imxiDH8Mr1zczVxNm44n/pcvL3+dgAUgncCw4SwxWNFTUZMxh1F4EWjRXpE20SwxUHFngZcx6HIn8mmC3kMi43YD0SP55CqECgQwQ/kztwNt0ufyZxHQYVYQq0A6r8TvU88lvsoO3e6TLs/uyr6x3wKO7e8m/wmfE17oDqo+ZS3sPYis5MyRfBn7nPtWevIK0LsTC3WrgRxm7N5dSU5Uvz0/ymC+oUWB6KJGwr4jGkLC8vsy1hJPwfORwQE5EP0AyFBzAFLgTEBNkJyAeTEFgNeBDTFjAWvBkJF4AVFw9iC90D0PqP8/PlLeDW0zfN0shnwBrDEr64wF/EBcfE0EbWjeFT56jytfpUAiwLFg5wFIgSchXOE10Q/xCYC6MJGAcVBSQGtgTNCj4ORRLNG+cjayrzM148Hz9uRuhGska8RAQ/NDtyLxYoPB5tEtgIvQDX9nzwau1i6Erqw+mR7EnyZPIv+zz7UP9sAIb/4v17+Krz6+nT4vTVAc1BwjC3oLHip4ykv6JDoRKtYLN7vJrPZtlh5335GAcKD94dhSFYJ4QpMynZK2cfMR/XGVYMbQnrA5v7c/up+4z6hv8EAwIKOhQSFOIgIB2FIXwk/B+OHj8XMg8HBWf8ve7I5ErZhsv4xim7u7k/uKq3Z8CqwLzLlNRP3H3owPD1+ED9JAb/BxIMOwweC4kK6wPdA/D9LPl9+U71d/Wj9y36ewELB/IQvxsoIhwsFjkoPINCEkjnRaFETkNOOl80dSi6IHIVQggGBM34w/LA8IXthOwC8MXzDfcm/qIA4AWGCIgJRwvTBZkDxPvS8/np2t4a1H/H2btdsW2qwKMNoeSgD6IJp7eugsCaxyDYf+lI8a//xA31Ev0XLR1sGjUZzxRwFBIMBwWbBFz+D/h0/G/5j/wDAq0H6gvRFV8aHSTFJ/0olSuWIykjlRrmEdQGffmu7eDi99ekzbfIgL+XvBK+KrzkwovGws991xvd9+jV7DT2EvqC/Pr73fqp++X2ePbP8QLw5O147WHwRvDi9Kb5//5aBvcLVxUeHJck5SokMQ40LjfkO3M4EzdBMios6iVqIcoZKxMSDKMJZQT1AX0CDQDYAL8BLQN+AxcGMwfvBpIH7ATcAob/3fp49k/tVehG3+zYdNFdy5bEf74ZurS1tLWKtKe1FbcxuFS9Csrrz8DWoeVH6L/v7vyS/hIDyAf6BIYIgQUbCXoJjAMpCV8J+gTAChIMiwsoEecSKxOfGFwYsxwIHzUZAxxREWkPXwk3ARL6y+7L5jzhQtxf1a/ULc9fzI7QAc3T0SbTAtYL3LjaMuNp5LLnJez+7J/s7uts7tbtpfBF737xPfO69ZH9KAAhBA8KBQw3EhMVuxg4G7Mcjx+FIRAklCKcJ+0n6iVYJzgkNSK7IasfbhsWF4AVYRO6DwgOqAxOB+wEpwPl/zT+QP1I+tr4e/hr9lD2kvV08znwrOym6Gnkzt8v2VzTAMwRxlnAibyhupu2z7U8tjy26LwxyZDJfdc/49nmDPZuAVcE7Q24DqsOKxPQDHsSOgvvBh4LdAXRBF8Juwe+CakNjg2HEewVgBXqHEQaGRnjGIcReBC8CAEBofYX7NTj5t2V1ezQb87sxyfLD80rznnUDtUZ3MzeWuNW6bXpRe+/71XxwPBV8QXySfIF8h/x4PO385f4av7LAIUHYguiET8XKRrSHnQfdiCTIXkiaiHYImsiaiEaIhcgFyDSHn8d9htcGHIVcBS/EhoRWw8iDUcLiAn/BwcFpQKG/8b8O/q+96H2dfTg87Txse9c7ZrpbudZ4uPbX9WYzvnHGsNYv6+6xrhLtz23rblSxEDKls3J3MjkL+r6+0UBdAUyD98Nug/zEZ8PeBDKCJQIUwqnAwwIXwmGCD0NQxHXECUYbBo2GscgKhu/G3UXyxFMDmgG4v0H84zp1ONs3XrVC9NIz1vKWdHf0LHVt9n82uDideOO6jLsQOxF7w7v5u7k7Yjv/+0f8bHvV/IA99f2vf+0A+MHZw7YEeIXzRv6HoMgxh90H/wfxB5UHI8fzhzBHDEfqx92ICkjryJcIVwhmx7CHXoaMxgEFDIPtQwPCnUG3AKHANP8m/vc+Q/49PdR9/L28fX+9d7yi/HJ7RHoIuLE2RfSMcn/wpi9crZts7+z2LLPtRPH9sUJ0nfkOOeE9aoFgwbvDvgUXRBZFoQPQxH7DYwDlQn6BDcBownxB3oJUhJVFMgYXiKsILQlMymHIuollxvFFoIOgAS1+g7vTuT13nDXCNGt06TNR84f15XVit8h4QzlSurE6mPxee6W7w3uaOy36hTqBuoF6UzrCuz48cr2qfvsBBsJARIWF7McryIpI4slsiQNIvwfLx7+GOIX4xiAFdYYbBqAHl4i2yTxKScqTyo2K3MnwCQmIbwZVBPvDq8I+AOF/uv62fdr9pP2J/ZE97/4zvkv+3T86/ro+JL1iO+z6GHfONY0y4XCX7uHssav0K1JrUOyd8Jyx6DTLOhF72r+Zw6UEccXshuSGPoV5hFbD8gHvQBvAuT+DP+2BHUG3gzOE8oZ/SA9JwArUyzrLl8rqicyIPsW9wtiAsj1Semz38PYMNEtz3LQBtD90rjas9/05hfs2u+L8WbzxvSX8GDv0+uw5q3kM+TF4rzll+dn65zzjPpUAosLYBIbGggfiiTSJ8UnWCf1Iz4fshviF70R8A9BELoP2hIlGBIdYSTVKTwvyTL/MvEy6y5bKTcj5hryEIkKBANA/Tn5J/at9TT2Afhl+7v+bgE8BIEFPwYVBfQA7fu381jq998n1CLIs70TtpqtNqqUqQ6qQbHxwnXJ0NgK7OX2xARIFFkWGxp8G6cUGhEbCewEI/wY9b/4bPfO+bQD8whsEWQdsSOwK3kzlDNGNXkzpi2OJ9wcKhKeBkr7zO8M5f7bLtg/0tPRstZ81tfcd+Q76TnwaPRQ9sj1WvTq8ZDrD+eN4Z/bqNg92fvZ6d/x5PDsRPexARIMchWmHCgiESWqJ8UnzCPiIFMbwhSxErgOcAuLC2UNvREHFpseIiduLHkzqzmrOUI7IjgIMJIpFR8uFbAJ5gAt+sXzEfGL8T3zyvb6+6IAgwY4CsELqAx8Co8FAADX9qvrz+BQ1JrHpr0rtKmuDKkzqNurgq9ouIfMaNLT4q31gvwSDI8WgBWSGMIUnA3MCQz/V/uq8wHv/fQ09uL98QcNES0d+ycVMB82kDm1Nyk0+i++I1MbFw/1AQP52O5R5jnfTtsj2gfZPtr330rhDuaE7EPu3vI98wXyK/Cd66bo+OB53bTXr9QO1WHW/tu546vr4/V9AvkM+xbtHgEj3SU4JIokqx9BGIwUtQy8CMgHawiUCKkNVxUDHIokSC5tNBQ4ojzXO5w4lDMbK2oh4BaBDSEE3fry9gfz+PFo9Bv3I/weAoMGOgusD58PIw7bCrYEFfww85fndtup0FPFAbx8tISwgq9krYeygbc5veXLMtvL3UbwjPrV/SAMCA5hClYM7ARsAJ79hPUl9VTwZPIy/VD/vgnFFn0c7yiFMpIySTe+NG4suimbHogS9Anu/CX1Uu8s6BrldOIi4kLlDOUR6FvstekL7b3uTeys7KfpeOWc4jnfn9uc2VXXfNbc19TaIeGm6Dnw2vhvAlYMHxSIGhQeFR9WHQ8brRgOEi4M5Qg8BBME/QZuCmkPkBeFIQwqMzLGOSg8UTyVPIs2+C6ZJVMbTxD9BqL/s/nI9Z/1k/aY+fH+wgNrCMMMgg5BEP4PmAsyBigADPby7f7kt9kh0KjHqb/xuWS2SbbPtYC2R71PwpzI99dG36zjdPOV96r8gwaYAgMCEgPt++78v/jW9Uf5J/Zr/54GHQokF4sc5SJ9LUctSC6AL5omayLBHMsRHQo3AWL5FvT17/7sSur36Erq0upK6tXsTew76Uzrpuij5q/lcuF73mzdgtr72bjanNny3MzereSd6y3xi/mv/2gGug9tEnQWuxjFFvoVfhTyECINHQrWByYH2QmfDw4SUBmII0Ap4jH7OFs6NDvhOUQ0wS2lJGwaxw8LB24BL/sR+Sz5Y/o0/i0DaQc7DPwOnw/GDlgNDglUApv77PIi6gnjPtoy0ifLzMSavg+8Nrv+uUK6s70JwabGMtJO27Pf/uxy8on4wAIDAm8CfgOD/fH++vv3+bb7ifi9APEHOwz9F9obyiKGKg8siSyiKxEl0h7XGV4RowmzAgj8UfcK9cPyVPCj74fuGu6f7EDs7epF58vmTuT64T7ipd+J3rDded1s3RDfzt9l4azjU+fw7HLyv/hq/iEEtAu6D0gUZhYVFnIV2xNSEvwOZAx8CqMJIw6wEQkXmh3pJGIt8zNMOa47rTq1N2oyACsBIyUY4Q6gB9gA4v1n/Gf8Gv/oAU0GlwqcDXYPuA5kDLAJ7ATk/r739e/o5+zh1Nr/0zvPxchtxE/C08D8wAnBJMEExvvIV9CV3djdR+gV80z0bAAHBcsAWgYeAioB+ANq/mABa/+iAMELPg76FbMcqx/PJckquimtKR8l6x28GTkTAwuBBXf+YPjK9tLzi/Gz8K/uoO3H7JzqxuuX52vla+Uh4YHi3+ED34zg299G32jjTePI5Nzop+nM72n16fkAAPgDVQvwD28TMRcWF/sWSxaNFRAT1Q+rDrcN7w7CFFwYsxymJSosazOCOTQ7QjsWOYUyLC29IjUZCg8JBrAAZ/wh+5v7C/4QAk4HAwvVD4cRahB1DkYKdAUY/v71T+0M5WDe99d00fTM+MbKw0/ChcKFwuTCHcX4xr/NL9mH3TLjzO+P89L7PgXEBN8ECwd9AgMCOQKHAK7+DQBoBi4MzBLoG/0g+CUBLNwt5itDK3sjURoVFt4MMAWVAH35DPYz9Vr0t/OD9PvzmfGl8Cvw/uw56LDmMOI64H3fHt+V3efe+OA84Xjlpuhx6ZPtBPGe9BL6g/1iAkEH3AtPEGET+hUxFzAWtxYhFQESURHTDvAPmRR0FhEciiSSKbkxBzjvOXk8nTl5M+su5yM4G9cQ7wbAAtP8FfwL/pT/qQR6CakNNxJwFJYSJhBHC50Fhf7l9nnuYeeA4Z/bLtgM1MLPX8xAyp7JTMnex4HI7cg0y0rQJdse3zPk9e8H89P8ZgWlAoEFaAbLAD4FsQGiAB4CKACVCWkPYxSpHuIgBydgLKIrsCv7J1kf1xmIEsAKWQXx/kj6X/fl9pP2hPXl9oT1qvNj8R3whe3q6KPm0+KZ4GPgjOAr36jhnOLv42Lo7epB7UbwFfNE9z78NgAtA20JwwzkEH4UZBUKGIEWmxXeFTcS8hDyENcQ6hTKGYwdfiVULQwznTkNPLA8aToANH0tKyQ1GTQQxwaVAHb9xPu6/RAC+wW0C7sQVRRZFi4VURHqC4EFTf259NPrTuTY3bXYodTT0TnOesw0yyfLrsu6ymnKJ8tTzVDU5Nwc3vTmEPC59JT/ZgXfBMgH4gasBjMHWQX6BNoBTQb7DRkQkhjfHpMhWihDK+Uq1SmKJPccJBddEIgJcQNe/zz7svhi+WL5v/im+Sj3j/P48Tnw+elf5u/jN94P3rPfe95l4VrjNeVY6q7tb/De8tLzOPjp+ar8UgFUAhoItAvvDrMTWRbgFkEY1hgxFzwVBhVvE8MVQhmjGuQhWCemLQI1+TfjOuM65zSSMlspnR+eFy4MTgfoAZL+NgC/AaoFOgvhDhIUnBbRFQQUFw/YCEYCEvqn8evpx+PL3TLbE9h51FrS689UzvjPKMzly0/LQssQzr3Uydwe33DoSfK+95kDoAcYB7QLTgeUCAwIPASBBbEB4AVnDuMPvhpMH5Qi1yrmK2AsRSylJCEehBiFEAMLZQTY/zD8Hvkt+n35VPlU+bz2t/MT8nzwnOr2563kPOFy4Vni+uG75F/mv+cl7A7vfPAV8z/0o/cg+rr9EAL6BKQKdg/aEtMWlRqTGXoaoxoWF0sWExV8E8cXXRkvHi4meCoONJ05GTvdP9c7pjbkMnImgB4EFFIJCQaU/8n+KgEEA+UIFg4BEmgXgxfgFpgTqQ0LB/H+NPby7YjmjOAm3N7YONaF09PR3c8I0RTQzs5Wz2/Op8+91E/cjOD+5Nrv7/TH/T8GJgfMCQ8KhgjACgwIGwmsBmgGuA7yEIQYqx81Iu0nUSs4LAMtTCheIvQaLhXtDa8IpwNP/lf7Lfp/+un5O/pH+ZP24PPD8g7vWevP6OLjJONZ4rjioOSU5W7nnOp47QTxP/Rp9fX40vvw/YwDSwVTCgoP1xAwFkEYyhnmGuYaUBniF94VZBXeFSUYphwIH2YnVi4aM9c7Nz1FPW09RzZ2MRYoLR2ZFEYK0wVSAXn/BAPsBLAJhRAEFOMYyhlBGM8U+w3jB+T+GfY17iflH+DX3KbXpdag047QxNAU0FTOK84AzMnLwc561QHeY+AU6tb13foYB/sN9wvHD0kMzAnNChcGHwOxAZsEFA1eETgbwCR1KNMwUzUdNaM0by17I0ccHhMbCfcC1f0D+fL2e/hI+rb7C/78/Kf62vgn9qXwrOy/5/rhs99+4KfgS+In5XznxusR8T3z1/aL+RT7T/57ATAFeQgGDRoRwhSSGM0bYhxkHcEcvBnvF+4WZhYKGAAaFB7dJb0rlDMLO8w9+D9lQLk5pTVfK8YftxYuDJ4GAQH//ugBEwS+CeQQ6hTlGb8bbBp1F8sR2QkQAlT5VPBW6Z7jmN//3OHaVtgR1wLWlNTx0+zQL9DOztnMCNGp2Xjc3+Gu7av0av4nCGEKCA5pD0kMPQ1GCtkJkQYVBc8L4w9XFbYeRCOtKSAuFTCDMRIuZyjGH3gZohEqCp0FhwCP/I77c/tM/J79nfzd+rD3NPYi80Ht7ep65o/iZuKq4tTjbeaJ5z7rUu+L8f712fce+U39yf45Ak0G5wmQDpQRwxVQGaQbLBxWHWAb1xn+GCUYyBgpGowdryK5KNEvVTb+On0+LT+wPH83aDHDJkgdzhPqC/sFOQIQAvgDyAciDb8SnBZ6GqMaJxm0FGcO1Aau/uP1ye0q55zizN4m3O/aE9gT2L7VX9V51CPRFNDBzpjOC9Pg2b3dGuUo7rz2ogB6CX8MuA7+DwgOWQ6aDEYK/QatB8ELNRG3FusdryK3JxAtPC9KLywtPCa2HuUZyxHBCzIG5gDu/I77+frd+vn6Evoo91r0MfQQ8Kzst+p65uPkGuWU5R3n9+gU6iXso+9y8hb0rvZg+ND6hf6YArkGiwu6D2MUdRfaG38dLR0vHkUb1hjvF8cXkBcnGX8d8SHUKKowijULO0Y+8zxqO2I20C4sJVEasRJhCgcFOgNFAcQEvAjeDNsTJBdCGWwauRfAEyIN4AVP/sb0he3o5zDizt953fvZWNm12ALW9NWh1NHQctCKzgPOrdM+2jTcGuVP7UL22ACFB4sL+w2cDYENSQyLC4gJLgTvBosLkQ+PFiAdhSFLJyosSC6MLmwr2iMgHe8XJhB8Ct8EhwBA/SP80/xZ/DL9L/sq+DT2CfQc7wrsmOhp5EvigeKQ48rl6OcF6fDsVPAi8071hvZ9+RL6/PzMAToDDgneDDQQgBXxGF8aVBxiHKMayBhoFzEXMBaEGBEcTSDeJjsuyjP8OSo9Uj3IOgc4Ly+oJiAdEBMgDMUFswJUAkoE1gfrDKIR0xZcGEIZGBgCE0oNrAYm/pP2Ae/B6GnkmeA33lvbddrc11LVUNRa0kjPpM2VzLzLStDE2ePbx+OW70z0DwFdCF0I0g0sC4gJRgoXBu8GfQLOAkkMWQ51F48fYCMAK4wu3y/6L9kr6SQRHOwVZw7UBh8Dav6O+5v7MPxn/JL+7vyn+jj4TvUR8WjsEum54wbhY+DP4Prh1uQp5rXpeO2z8Pvz1vUe+d36x/2/AXIEUglYDV0QpRN0FoQYnxjXGdQXwxWNFSIWqxcpGpseDiMzKSQxHzarOVE8/DkTN08yoSrWIU4YrhCXCloG0wW4BXkI6wxPEEkVChhQGZ4XBhUKD7wIRgL5+uDzu+0F6XjlnuMi4tvf8tyf2xPYX9X/0wTP5cuTy07KUcy+1Y7ZLeAj60ny+vtZBQwIBg1xDG4K9wtpB0QJxwZ+A5cK0g29EVQcZR4QJE4phClTLF0q+CV0H68ZihMjDicItgReAJ38nfwg+lb6R/ld9nTzIfJS79Pr7eqy53jl8eTW5HjlfOc56AXpuOu77VLvf/KE9dn3V/t5//gD8wjEDV4RmRR1F8oZ8RhrGTUZ6hS0FDoUtBSrFykagB74JSgrCzKaN8Y55DuOOBA1FTBzJ+0eBxY+DkYKMAXEBLkG4wcgDJMQmRR1F5AX0xZhE8QN/wcBAbP5m/L86w/nx+Mh4czeatxM2vfXbdVe1LjR6c6kzV/My8wL0/za5NzL5pbvXPVFAQsHdwcgDLAJKQmVCfEH/wfQAwwIPQ0lD5MZtR3wIAko4SjyKg0r0SYZIdkaqBUlD5UJ1AZ7AXf+dv1X++37V/tT+OP1B/O08TTtPuvr6TXlJ+VQ5V3l6Odw6LXpguuF7dvw3fGe9PT3ffk0/qUCrAZxDJ8PsxMHFvEYNRknGfEY7BX4FFUUmRSEGBsaqx8iJ64qlTSdOcg6fT6EOmE1QTIUJ0AgBxYvDecJwgN0BdQGoAcWDlERPBWhGbsYGBiYE4ENQQcbAIn4wPBY6oblgOGl36LdgtrS2W7WJ9TW08XRzs45zrDMKs1S1VvbKt5W6SvwePbaAXQFzAkeC8oIHQrjB1IJhgjsBFULCA6HEUccuB/nI3UoJSmTKtUp3SWPH6EZzhMvDdgI1AaJAa7+Jv62+2f80vsP+Az2f/La7xfsc+rc6JLkuePj5Lvkiedk6Zrp1ex57lTw0vNC9pf43fqv/+kCrQdKDQsQ6RM9FjMY4xjKGTUZjxZyFWYWIhZCGUoeJiFYJzsuoTOpOP87TzvSOFI0Vi6LJTsdSRUUDZQITQa4BcgHOgurDucSPRZBGCUY0RUoEcwJpwMV/J70KO725/3jBuFv34ne8ty42mTYHdZ61RfS3c+kzRvMmM6h1Kzbp+Bk6fjx+frTBTYJgQ2dDhELtQwpCQwI8QfAAjUI+QyTEB0bmx7bJCcqayrOLbwqjSYlIHUXsBERCyMFbwKR/fn6tfoS+mX7Ifs5+Rn27vOn8Sju0+uY6DXlu+TI5GvlOej36Ajrau2j79HyQPWH93H6dPzYALYENgmCDmwRpxR1F8oZoRlsGp8YthVkFX4U+hUpGsEcKCLvKKcu3DYzOpU81ztkNwwz5SprIkIZ4w96CaoFmQOdBScILgyTEFcV1hhRGpMZchUXD3kIAQFH+Y3yI+sp5iTjLuFj4Jjfvd3+23PZ3NfN1ibTIdBjz3rMws8F2HXa3eBk6Snv9/liAu4FAgpECQ8KlwptCdwLdweFB3EMuA4HFqQbIR7KIhAkByeqJ4sl8SE2Go8WKBFkDGEKIwVFAXn/aP24/Kr8mPld9knyEPAa7t/qjOmw5sjku+TK5Szocek96lnreO2x76fxdfQn9h34Zfvx/qcD2AioDLoPYBI9FgkXkBdrGVcVZBVyFacUUBkPG5seiyWfKTIxLjf7OP46xDiIND4w7SeRIIMX7w6JCscGMAV3B+UIIAwNEdsTdRfvF6oWpBIvDccG5f8D+YvxCOtd5SLis9/Y3azb+dgP1ifUQdO20OnO5sy6ypXMntJK2VLeQuXW7Z70g/2PBfsF1gdBB9EExwZZBT4FPAQXBvkMbBEbGjQh9SMlKUIq1yrJKiwl7R77FngQfAriBtADXgDH/U394v1o/V7/L/uw91r0OfAL7RLpbeZX4QTgOuCo4UHkRObo56nqoO2K8NLzXPWJ+Pf5JP0qATAFHQq1DP4P2hJ+FFkW0xbuFhMVmRTsFe8XUxsXIHwk/insL6U1+zhAOhY5RDTdLtQorCCDFygRpAp3B3UGdweXChQNyRASFNEV4BZXFUMROwxLBa7+9fjs8jTtO+nX5e/jMuMT4b/eGdwF2KPVhdNy0InNG8yfyjfNGtSc2bDdi+jJ7UL2vf/pAiYHQgieBuMH4gZOB6wGtgTZCVYMUREnGXAcXCF8JJklZidkJtgi3BzHF/USmgx6CfsFewEo/3b93/vf+8L6RPcl9VfyiO8y7NLqEehc5E7kx+Mz5G3mAufb5z7rQOyv7o3yXPXL9zz7hf7AAiYH6AqpDf4PsRKlEwQUIhbOE/UStBRwFCUYmBwlIH4lhyu4MKY2+zi5OWQ3XjN+Lo0mFR+eF8cP2wpQCCYH8wggDEwOexJXFcUW1BdXFdgRVQsHBa7+9Pc88oTs2+eh5eLjIuKb4RDfXdzg2RHX5dS40VbPsMx4y6XOyNPg2bPfHedt77D32P91Bl0I5wk2Ca8IUgnvBpEG0wXHBvcLQRAxF8EcaCB8JOwmCimQKG8kuB/XGcwStw0ACfgD5f9M/Dv6s/mY+RH52fet9fvzLvJG8EPuuOtV6IjmUOWE5Bvm1+UA5s/oZequ7VfyTvVi+UD96AGPBSoKMQ52D4cRfBPaEmETEhQBEm0SNxIuFU4Y9hv/IdEm9Sz/Miw2TDmQOeg1NTOwK3AlSh6NFckQRwtfCV8J9AkjDrsQSBSEGMgYeBm5F3wTWQ5cB7AAEvrS8/LtZOkO5jXluOIh4VXgDd1b27XYzdbI03TRBM9uzcHOu9N913jc/eOA6hPy3/uiAOsDDAjWB6EI9AltCUQJ8QdhCqkNeBC5F6MaLx57I8Ak3iY/KCwlhSGnHe8XzhORD1MKJAYDAnn/Cf2b+wb7Afh39Uz06vG/7zXu0+vB6H3osOYO5mHn5+b05gXp3+r+7CvwMPPl9rP5yf73AscG3AsjDvAPRhMfFJgTSRV+FB4TBhXPFHcYixxAIDolNiuqMIg0LzhAOi43AjUJMdUpRiSYHI0V/xC3DeoL3As+DngQKBFyFeAWWRZZFpYStw0bCXEDkf3a+FjzRe/G60rqcOgO5kHkPOEB3oTbqNiI1U7TV9BIz/fOjtAd1pHbOd8D6MzvufSu/nEDWgbZCV0IyggdCoYINgniBogJSg3hDu4WYBvCHQ4j9SMwJ7cnsiSgIQMckBeiEesMDgkuBKL/nv3t+zv6tfpu+Hj2hvac82PxBPFc7T3qcOhf5m3ma+VE5r7m2+eC64XtY/GG9pf40/zYANEEhgg6CzEOJQ9DEbESeRFvE1QTXhHpE8IU0RUAGqcdRCPgJyosTzLMNGQ3IjhrM/0xOCwQJOEf1BfaEpAOwQtzDXMNeBBGE2QVGRknGbsYnhfaErcNDAh9Aj78vPZk8uTtdOtW6VHm/uTf4TbdTNoC1kHTZdCTyw3MW8pdy/DSEddD3YblxOru8/r7//46A3EDswJXBKUCpwMuBLMCkgcDC2oQJxlTG/EhiyVjJbopgSc6JUEhKRq3FhoRFA2yCuwEzgL0AHf+d/4y/c75h/da9HDxDu9o7FbpX+ag5NPi++Jo48fjCuS85b/n+em77cDwMfQB+DD88//4A3kIeglJDD4Ojg1pD58PJQ/+D/APUhJJFdcZgB6iItInmC3hMEQ0lTReMwkxOCycJ4UhAxw9FvMRnw9ZDkwO8A/JEAITVRTqFJsVpRPXEN4MhgjEBA0Atvtu+O7zLvJ77/7sc+qV5lniKt4i2YbU7NAPzfzJZsi3yBTINsx30/fXQ90b5sTq0fL5+uv6a//LAP/+ywCHAEMAKAAa/xMECwdkDCsTnBb3HAsheyONJjAneyO4H3oafhSCDikJjAN3/i/7LPnX9rL4bvjx9Q33XPX68nDxDe7D6V3lxOFg3rzcvNxp23jcSODu4onnx+zb8Hf1zvkX/eX/LQPRBKkEMgYLB6wGNQjnCcwJfQupDWoQVRSGGQUd/SByJq4qOy6PMNMwBi+kLBgpzCMvHuMYpBIlD94MfQtJDIENFw8oERATBBRIFBwS7w7MCVkFUQAG+672PPLz7mjs+uqn6QPoreRy4Q3dSdgm0/XNQMqyxaLDAcTJwknHHs431WnbFuNY6rPwe/iO+zz7uv2A+5j5Pvya+mX7tfom/qkEKQnkENEVhhm4HwkgeSIBI/oeKhuZFHgQsgrgBZYBQP0F+h34J/Zp9a72WPP48aXwGu4K7Jrp8+W44lTfNNwL3MbaW9vG2sncfuDU4xHohOx88Bj1v/gV/DYApAFvArQD0AObBOwEjwWRBgsHUgkuDOMPSBQZGcEcuyF/JhkqsiyzLb0r8SkuJvEhwRy3FuYRxA3oClMKAgpiC94MnQ7yEL0R5hHXEO0NzAm4BWwAxPtE943y8+5N7Abql+fX5cXiOd+d2h3WZtEAzD3IlsT8wDLBaMEXwe3IPNCg06DcnuN/6ajy4/Vu+HH6U/j1+A/4Rfjp+df2PPvmAHIE0g1gEoMX+R0VH6IisSORILMcBxaHEQMLZgVuAUz8pPhR98j14vQN9z/07PJw8QHvTeyL6P7kOuAL3OzYYtc41vbWpdbQ2BvdY+Ch5RTqr+5/8jT2ffn6+67+Xv9e/7AAlgGxAVYDtgQkBrwIAwsmEJgTThhKHgsh+CWhKios9SwDLVspwyaUIuoc4hexEtMO3At8CqQKmAuoDEAPCxDyEFERQA8vDcoIPARQ/wb7rvaN8jfvJu2p6tzol+fH45ngQtws1yPRKMwgxw3DqsBYv9K/PsDNxSHQDNSC2srlceml8GD4evdx+tz5XfY295P25vdf9yr4r/9xAzgK9hP9F4AedyFrIh8lyiJYHkEYsBGLC48F5gC6/W/5lffl9nf1bvj095/1JPS08UPugOrZ5j7i8tz52OjWRtYD14vXStlD3TzhX+Yx6wLwnPPy9un5+vv//l7/a/8NAA8BbgHOAoEF4gawCc8LyRCAFa8ZPB6FIRElrSlsK0UsASzjKTAnDiMlIL8bWRbAE9cQrA/+DyYQsBFSElQTpRN8E5YS7w4DCwsHHgK7/iD6Xfa38y3x8+6s7DLsz+g15RPhTtv01ezQucmyxQ3DWL90wLrB2MO8yw7VWNlZ4sbr9e8N97X6MPzd+kf5mPlQ9vL2ffm89gn9EwQ1CFIS1hiOHm0jtCXgJ+olryJ/HSEVURHZCcIDOQJA/cL6c/u1+qf6CPwU+2D4Qva381Du0Omj5hLgT9yQ2hPY0Njt2SXbEN9a41PnTeyz8D/0lffd+p38/f3K/+X/egBFAZkDcQODBr4JfQtbDx4T+xajGmUenyDaIxQnrSk4LKIreituLE8qMShJJuIgwh02Gk0XVxVgEm0STxBdEKQSsBHYEbARnQ6BDW4KQQcuBIb/qfs29+/0z/FD7qvrHui44szeuNr/05rP/srqxm3E2cSWxHzFTspS1cPYpd9b7Fzt5fY0/vn6KP+6/aT4V/u+9zv69/mn+gcFDAg3EmAbZB3tJwop+yfZK3AlgyACGxATTA4MCAcFmAK9/+YAbADk/rMCvQBN/YD71/Zk8sfsBel14znfNNyd2iXbNt3m3evgNeVV6EHtwPAW9Cj36fmO+yT95f8qAdgAHwO2BBUFDAhHC9AMNBB7Ek0X2RqpHogjSCXhKAEsOS34LiAuOS0bK54oByccI6sfpx30GkQaaRhcGMgYFhfUF9MWZBV+FPMRWw9xDJUJTgcuBHsBef/6+1T5a/Yw873uVumE5L/ejdiS07POGMpaybbHqMe5yULLR84H2UPdV+Ex6yjuaPRK+1b6dv1Z/HH6+vv3+UH+g/3H/aAHmAthEwUddiAwJ3cpNCobKyInUiPLGowUGRCwCeIGjQSlAugBfgOlAtEEEwTLAAj8zfiB89XswejF4g/eQNt12p/bbd7b3+Dibue466Pv7PKE9QD3OPh/+n/6g/2F/uT+UgFKBO8G9AnEDTQQRhNkFa8ZLByAHuIgXCGxI1gngyg5LVMseyyPMPUsfS2YLVUlsiS4H1MbABqAFUkVyxG9ER8UexK0FMIUQxEqEqsOjAyVCd0DUQB/+ub3B/M37+7riOYu4djdtdjI00rQ78nSyCzGBceNx5rHKMym19DY6d9n64LrFvT3+fT3Z/xj+qH2A/mH9xX8PvxN/TYJcQwGFT4fCyGSKU4pkCjxKdskkSAAGhIUkxDZCc0KoAd0BQwItgQ6A4MGvwHV/en5TPTz7gXpX+ZK4XndGdwW2gvcid4c3tHh1OOJ5wbquuzn78LxnvTK9vL2dPzh/Hb9zAHOAuwEhQemC7cNuxDOE1kWGxrfHp0fuyHPJUsnhCnJKuYryyvlKjQqPyhmJ1QkFyBYHvccNRnHF9MWHxRIFL8SsBFeEf8Q+w2aDBELlQmDBmUE9QHw/dL7DfcJ9Hzwc+p45c/gW9th1sXRvcy6ygjJWMjSyKvJGct6zHzWnNnJ3K3k5+Zb7An0z/EA9071+/Py9oT1O/pl+9/7tgTlCOQQhhkeHIgjHSRvJEYk1iGMHVoXARJMDikJowmeBj8GTQY+BTwE0QSYAmj9YPiN8njtA+h14+feGdwI2pzZ8Nvm3X3fBuEY5IjmR+jt6qvrx+y97lTwLfFp9cr2i/ll+1D/pQJyBB0KzQoWDrsQsRJLFv4YABoUHnQfNSKoJo4nayobK/IqQyvxKe0n2yQyIIwdAhuPFrYVsxN7EnsS5hFtElISbBHXEBYOEgz0Ce4FHwOS/tD6lfe28ufvZ+sp5mbild2a2CfUpc5OymPG88PnxLvCecP1xPXEJNLZ1SvWCuTu4pfnp/HW7XLyfvGH7i3xYO++97D35veqBVoGrA9sGvQasSOvIpMhYCOOHhId+hXVD+8OGgi8CEIIPgWeBoAEewEfAwEBjPrG9G/wIuqs46jh/tsg2DrXDtXA1tLZPtoZ3L3dtuE/4yflOeiY6Erq8Oys7Jnx7vM/9B34SvvJ/isCkQZfCfkM1Q8rE/sWGxqXG3Edjx8mIXwk7Se5KJ4obCvXKsgpoivqJa4hFyCjGpwWzhN5EXUOmAuaDEkMtAsvDQ8KAAkaCAcFpQJ3/i36XPVj8azspuh45UbfZ9pw1wvTzc2hy8/GbcTYw/PDAcS+xG/FPcj80eLSt9lv30rhYugZ7Q3up/FG8OnwSPFy8h75y/eC/DwE1gf/EPsWshs+H8Qexh8gHcoZqxdBELUMzAlLBeIGcgSpBFkFzgJeADYAWfy89lXxMevW5Pffld2o2GLXU9a+1ZrYCNp43AHezN4w4tPiCuRt5pXmweiA6iPrivAu8nX0A/mO+3n/OgORBkQJtQyCDmASYxQYGB4cIB2sIBAk+SZMKAwq4ym5KPkmBSbJId8ecBxpGMUW3RT2E0USbBGFEJ8PFg6oDCoKMwdKBBwB//5X+6T4n/UH89rvCuyM6aDks9+E28zVY8/XyyzGk8LHwUzAMsG7wvXE3sfOznzWpdaW3lrj7OHE6p3rR+jy7Y7qdOsC8H7xRfiJ+BwBGgjPCwcWuxiIGo4e9BoCG7wZfhRSEowMpAqUCEEHGgjuBZEGrAZGAswBogCX+JD0r+4R6BbjRt/w25rYtNfq15nX1NrX3K7cK98G4SHhdeMk42jjhuUp5m7nt+oo7rHvFvTa+Lb72P/sBHUGOAoUDasOhxFjFO4WGxrCHZEgsiQxKKEqhytuLJUr4SgiJ0QjIR4eHNYY6hRVFDkTlhLYEZYSbBHVD2kPIAy8CJEGbwKF/sL6vPYi88zvF+wD6ArkH+D72ZfWWdGTyxTIDcNMwPq/wr6pv5u/kcGOyHHPgNDG2g/emeBV6Ezr3+p57vzrI+tB7drvCfS59Aj8fQLYCNoS4xhWHYUhdiDiILYeyxqAFUEQ6guhCFoGoAeqBWkHQghNBtMFdAUAAAP5q/Tu63fkY+Dv2gPXldUa1OfVw9jU2oXcid5j4JvhuOIJ49/hFuNo46zjiOYv6mjsK/Ct9ab51f33Av0GXwmaDAsQbRJVFIYZLBwhHm0jjSYKKTgspi1vLUUsoSq5KG8kkyEvHiobhBj7FtEVOhRGEyoSeRH8DnMNpArvBiEElgGR/ab5QvYH87/vZ+tV6Kzj594K2yvWWdEPzbfI2cTJwqDCrsK9wzjFl8X7yILRx9Kl1szeUt4J4+vpEukX7DXuQOz/7cDwTvU4+CD6pwMkBjIPWRY1GbUdWB4eHCwcGRn4FCgRjAweC3cHAgrMCVAIcQyICT8GxwYrAn/6rfXY7gLnquIe3wvcxNlp26nZrtyl3wPfm+Gb4S7hjeGA4cLgSuEH4oPjhOS16cntou4Z9rP5qft7ATwECQZtCQYNxg7JEO4W8hlkHYgj3iYZKn4uVi5LMPgu2iyuKn8mHSRoINAdcBzlGTYa8hn9FwwZqxdkFR8UahC1DJQItgTYABX8e/i59Hzwk+2M6bzl+uHJ3MPYyNNvzq3KwsZew2rCuMCDwQjAx8FTxZPLOc4O1WfaQ9285evpjurY7jTtq+ui7jTtm/KB85X3QwAVBckQdRfcHNgi8SGxI/8hzhwAGmMUFw+rDnAL3w1KDcYO8xFAD3YPWA0mB2ICPPu28mjseua24RDfXdyT3IXcRd6Z4FXgS+KA4SHhjeHr4Cvfit8E4KXfdeO85S3p1ey08Vz1jPqv/9wCuAUCCqkN/A6xEoMXvBmdH+cjjic5LcQvuzK+NIg0NzTuMEctXyveJh8ldyGCH8Yfmh3rHesdORx6Gk4YBBSTEOoLGAdiArr9Vvrx9bbyb/Cf7IzpXeWn4J/bONYh0BnLOsbWwk/C4cBQw1/E6cXSyFbPNdQd1oTbot3n3oTkKuey5z7rkOus7MLxa/Zn/Az/IwWLC/AP1hiXG8Idjx9lHsIdgB7NG/IZhBjFFvsWnhfUF+AWwxXDFRkQTA70CUgDx/1u+HLybO646zno9OY15aDkueOE5P3j3+GP4n3fs98f4H3fit/d4Kri7+Ms6PzrUO6Z8UL2D/id/DYAsQGeBogJPQ1gEsUWIB2FIT0nEC22L70zBDajNBE2UjQVMCMwsiwbK58p7yjvKD8oMymOJwUmOiU0IacdRBofFF0Q3AsYB98E5gCs/Tv6ofac8wHvxOq85efeI9qG1OnO8ss8x2HFb8Xzw8/Gz8ZjxoTKqdAk0ovXhdyg3BPhbebZ5mXq0uov6v7spfDX9j78vf/KCD0NtxbcHOIgliOgIVwhMiDfHvccRBoAGvIZbhupHpEgIR6sIH0c1hghFbcNuQZr/3H6aPSn8eburu2R7GjsTewj647q2+cO5o/iBuGV3b3dDd2T3KfgV+Hi4yDpF+y97j3zhPVT+Ej6NP6iAPgD5QgiDZYSoRn6HuoloisjMDg16jY9OCM50DcfNgA0CzJNMXEugjCOLz4w0zDTMC8vEi5RKxQn1iEeHDEX1xDQDIYISwWkARr/7vyY+UL26vFN7PPlb9/e2PzRvMvdxkPDx8HwwbHELMY/yUDKOc53063TINhz2S/ZeNzb32Xha+Wy5y/qHO+P8z78hv8yBrQLeBDUF24bdB92ILgfdiBPIbgfuiDGH/wfriHYIhMmHyXnI74jIR5TG1cVCg8aCH0CW/3B+eX2afVa9Jvy3vJv8HvvdOtH6NflSuHn3q7cNNxA2wHe+OAw4g7mjOkK7GzuSPHR8sXzo/ct+rj8KwKFB94MYxRFG/8haSn1LGszADR/N8M39jXBNik02DPYM/EyyjNGNSk0jTcCNQI1GDKnLmwriyWfIG4bPBXLEbcNbgqvCMID9QHw/cH5afWi7lXo+OAW2pTUK86fylfHRsVVxgXHnsl4y0DK2czNzbbQndFB0zfVDtVm2Q/eH+Ch5cHoCOu08br1QP30ADwEVQveDBIUdRe8GR0bORzCHZ8gQCAcI68ioiIFJoslWCcEJcoioCGJGykagBUlD7QL/QYGBNoB8f7T/Kf6RPd49mTyAe9n60XnNeUw4iHhpd/13jrg3eD74sfjeOUA5onnz+gx63nuDu+P87D3ZfvpAkIIVgyYE8gYSh6+I+wmhys5LfctnjFLMOUzhjOhM8A12TQUOC84cjdzOH42lDOSMh4t1yqyJE0gmBycFowUQRBkDF8JSgTYAPr7Gfan8X/p1OPX3JfWWdGHzODIBcfnxATGtMaNx3PIS8hMya7LDMtUzprPp88Y083W7NgD3yLiG+a36g3u4/WY+e78wgMVBdsK4w9SEu4WMRcpGmQdVh3WITQhuyGxI3sjmSXAJCgiDiMtHTkc8hnOExwSSQzMCXcHwgM5AuT++fqY+Yb2PfPM7zHrz+it5P3jWeI64Pffs9/d4KjhMuPW5OPky+bc6I7quuyi7jrxkPSy+Mf9igLxB2UNsxPlGUoeUiPDJsUnNCq9K6IrUyx7LH0tEi6dMP8yrzPZNPQ0ADRBMusukypwJdMflxskF4gSnw8FDEQJqgUEA7v+6Ph088fsDuba3t7YXNMEz5XMDcxPy/7KsMy8y8nLQMqrySXKcsf8yQ3Mk8sI0VDUwdf/3LTgrOO+5tvnk+2U7rTx9Pd7+OX/BgQnCMYOWw8tFKoWdBbZGq8ZURroG4gaZR4FHc4cqx+8GYscNRl0FrQUnw8xDvYKMweeBn0Cov8Y/tz5zfjG9GPxRe8I6yLqR+h65q/lQeRQ5ZLkXeW+5pTlX+ay55jo6+n861ztK/BL8+b37fvLAGgGbQnjD2ETPxcNGrMcmh0XICYh5CGWI0glMCdMKFEr2SseLaQsDyz+KYEnVCQyIHAcyBguFbAR0w59C1IJaAb3Asr/Svt49iHyuuwd54/i2N0W2ovXAtaU1P/ThdO50t/QIdBizpjOHs45zt3PMNFc09nV6tfG2kLc892l31fh1uQd5yLqou5+8VD2Svtq/vUBjQQXBrwIHQq1DDEOQRDzEZgTjRVNF+IXuxg/F8UW0RVvE20S/g91DtAMiQpGCqAHuAUTBBwBXP5Z/FP4ofZL8+rx2u//7YXt4uxA7E3sguuC6/rqWOoW65zqxusL7RrumfHS87730Ppq/okBWQUmBx4LfwwKD1EREBO2FTMYvBnBHDweCSCgIaAhoiLkIQshgyBKHmQd5hoZGeIXSRVUE8sRuA5KDVMK4weNBKIAuv1H+Wn1fvGu7evpied35NTjMuON4ZngEN943DHajdgD127WytRr1B3WYdZV1y/ZW9uR25XdwN9V4BXiueOS5A/n6+kK7FTwqPLI9Tn5c/tc/r0AYgJLBQkGoQgdCsAK3gy3DfwOrA9BENcQQRA0EF0Qxg4jDiINHgthCv8H7wabBKUCNwF5/yb+/PxX+/f5ifg296721PTU9JzzcvI88jzy+PEu8uzygfOe9DT29Pc5+dD6dPxP/vP/6AH4A48FaQcpCSwL3gzTDvAPhxF7EpgT9hOnFJkU+BQuFd0U+BTCFMIUpxQEFJgTlhKHESYQ/A5YDXALaQepBJkDOQLW/k39V/ti+Zf4vPaE9ZzzOfDW7eHrsudr5RjkB+L64UviPuKQ41rj7uL64Qbhpd8B3svdy92J3vff+uEY5B3nVulA7K/use9V8Unyj/OD9K31o/d9+dL75P4BARIDdAWeBjUINgkCCmEK2Qk4CqMJXwkPCl8JiAl6CVIJDgl5CEEHTQZyBLQDKwLLAK//Jv6s/dP8TPy4/N/7qfvE+0r7Ifsv+8L66/oU++37j/wk/Vz+Nf8NAEUBOQJ+A3IEWQVaBoUHQggOCdkJRgpVCzsMFA23DXUOhA8mEMkQNREaEfIQkxCFEE8QWw92D/wOFg5KDZoMqAwRCw4JuwdZBRIDpAGG/zX/Qf4J/fr73fqX+K310fId8BruhOzu65zq+uo96j3q+enq6B7o5+b+5O/jrOMJ44PjQeTX5Srnceln6/7sNe5t70bwLfHq8ajyt/MY9Yb2v/ia+oL8Nf9sAB4CYwMhBHIEmwSNBMQEjQRZBUsFFwbiBv0GkgegBxgHuQaBBbYELQNGAioBXgBDAF4AbADmAGABsQErAh4CHgKWAQEBlQBDADYAegDmALEBYgKMA7YEjwWeBu8GXAfWBwwIUAi8CCkJ5wnoCvcLBg0IDu8O1Q/+D9UPnw9pD/wOxg4lD9MO0w5ND2kPrA+sD0APZw6BDeoLsgobCUEHFwYuBC0D9QHLAKL/hf52/fr7jPoD+Wz3uvXu89HyY/Fv8Hvvve7y7SbtW+yr6/rqjuoU6qfpVum16Qbqqeqr61vshe1Q7gHv5++K8EjxtPF/8qrznvQZ9mz3zfg7+iH7dPwy/fD9kv7x/ob/AACHAFIBpAFiAukCHwN+Ay0DBAPOAkYCOQLaAb8B6AFiAkgD3QPfBDAF4AXgBRcGxQUwBd8EgARKBI0E+gSdBXUGaQdQCEQJAgqJCugKAwsDCywLfQsFDGQM6wzEDZ0OhA8mEMkQNRFDETURGhGuEIUQXRAmEEEQTxB4ELsQ/xDyEKAQ8A/vDoENSQzAClIJyAeeBnQFtgTdA84C6AHLAF7/GP5M/H/6v/g29631q/Sq8+zyPPJj8dvwHfAp7w3u/uz86yPrnOpY6nPq0upM6zLsJu017qLuN++W78zvEPBG8LPwY/FX8oHz/fSG9vT3R/l/+mX7+vt0/J387vxA/Z79Jv7k/sr/hwBgAfUBfQLAAsACwAKYAm8CbwLAAh8D6wPfBJ0FgwYmB6AH1gfWB/EHoAd3B2kHXAe7B0IIlAiVCbIKRwtWDAYNcw3SDe0NIw4WDjEOZw5nDgoPhA/VD5MQGhHLEfMRARLzEbARhxEoEckQXRA0EOMP4w+fD3YPhA/8DlkOgQ1/DHALAgrYCGkHTQY+BWUEcQOlAokBlQBe/xj+nfxK+9z5bvhf9132d/XU9DH0j/Oo8gXy6fD17w7vbO6g7SbtC+007Wrt5O1Q7gHvUu/a7znwYfB88KXw2/BI8d3xm/Kq87n04/UA9wH4HvnO+Tv6tfrQ+iH7ZfvS+zD87vzH/ZL+Xv9DAA8BYAH1AW8CwALAAtwCLQN+AzwExASqBVoGGAfIB2sIvAgACRsJRAkpCV8JlQkPCrIKVQsSDPkMxA0+DuEOFw9ND4QPdg9AD00PWw92D/4PTxCuEBoRXhHYEb0RyxGHEUMRoBA0EJ8PaQ/8Du8OnQ51DhYOqQ0UDTsMfQuJCm0JQggmBxcGFQUTBB8DVAJ7Ab0Ayv/W/sf9gvwh+0j6A/nZ9zb3a/a69Rj1aPTF897yZPJ+8R/xfPDn73vvKe9F723vv+8r8G/wEfE68YvxBfI88n/ym/IV85zzMfTU9Lr1ofaH9274Hvmz+XH6wvov+3P70vtZ/OH8aP1c/gz/5f+iAFIB9QGKAhIDVgP4AzwEmwQwBZ0FMgbiBq0HQgjlCJUJHQqXCugKAwuYC9wLEgyaDAYNnA37DYIOMg92D6wPJhAmEE8QQRBdEE8QahBdEGoQkxCTEJMQrhCuEHgQhRA0EMcPMg/vDnUO7Q1zDcMMOwyYCwMLKgqwCdgI8QcYByQGMAVlBEgDVAJuAV4Ahv9q/p79gvzS++v66flH+Xv42fdE95P2yPXv9Ez0WPPR8jzymfFI8R/xOvER8UjxfvHP8TzyZPKb8t7y+vI980vzdPO38yT01PRA9Rn25faV9274Efmm+S36tfov+2X73/uC/Lj8aP0Y/tb+ef82ABwBvwGlAi0D0ANyBNEEZgUJBk0GGAd3BycIrwhfCQIKbgpHC7QLBQyoDOsMWA2ODfsNFg4+DpAOkA64DvwOMg9ND1sPkQ+RD6wPnw+sD3YPaQ9AD/wOnQ6dDoIO+w3EDVgNIg2oDC4Miwv2CnwKzAkACbwIyAfvBjIGZgWbBLQD3AIeAkUBogCU/+T+1f0y/YL8xPsU+1b6zvkR+W74vvcb92v21vUz9ZD0CfSB80vzFfPe8vryB/MV80vzdPO38+7zFvQk9HX0aPSQ9Ln0GPVp9fH1Qvbl9pX3AfiX+Dn53Plj+tD6Zfvf+4/8xvxb/eL9hf4a/73/QwABAcwBbwISA+sDmwQjBdMFdQb9BoUHGgiUCF8JowkCCkYK9goeC7QL6gtJDIwM6wwiDVgNSg2ODY4NqQ2cDdIN3w23DZwNjg1zDWUNWA0iDSIN3gzeDIwMZAwgDKYLYgseC1MK9Al6CcoIQgigBwsHdQbgBRUFjQTCAx8DfQKJAcsANgA1/5L+x/0X/XT80vsU+6f6IPqL+fX4OPi+9w33ofYn9pL1CvWr9Gj0FvTS87fz7vO38+7zCfQ/9Ez0aPTG9Mb07/Qz9Vz1hPXx9Sf2a/aG9g33UffZ92D4svgs+Zj5IPqa+hT7tvsw/O78QP3w/Wr+8f6i/+X/ogBFAcwBfQISA7QDSgTEBIEFFwasBkEHoAdrCIYIAAltCbAJ9AkPClMKiQqyCgMLHgseC2ILYgtiC3ALfQuLC3ALpguLC30LVQs6CxEL9grACnwKYQodCr4JbQkOCa8IXQj/B1wH1AZNBuAFMAW2BC4EcQPcAlQCiQHLAFEAef/k/jT+dv38/D78m/sG+zv66flU+b/4D/ij9zb3rvZQ9sj1QPUl9cb0aPQk9O7z4PO387fzt/PF8+7z+/P781r0WvSr9Mb0/fRc9Xf1n/Xj9Rn2a/bK9gD3RPej9/T3YPi/+Cz5Yvn3+Uj6wvpK+9/7TPz8/IP98P2S/ij/yv82APQAbgEQAooCLQPQA0oE7ARZBfsFaAa5BgsHkgfxBycIawi8CAAJRAltCaMJzAn0CTgKOApTCm4KwAqJCpcKlwqXCokKpAqJClMKRgoCCswJiAlSCfMIeQhQCP8Hdwf9BloG+wVmBfoEVwTdAy0DswIDAmABywBDAJT/u/40/pH94fxZ/Kn7FPtI+sH5Ofmk+A/4lffX9lD24/WS9SX1xvRo9CT07vOq84/zgfNY8z3zS/M981jzgfOB88Xz4PMW9DH0dfSQ9Mb07/SE9YT1rfU09ob21/Yb92z32fcq+G749fh9+dz5SPrC+mX7Ffyq/CT9uv1c/v/+hv8bALAAUgHoAW8CHwO0Ay4EqQQjBZ0F7gV1BqwGCwd3B60H8QcnCIYIvAjKCBsJXwmjCYgJlQmwCb4J2QnZCfQJ9AnMCdkJvgmVCXoJKQkbCfMIoQhQCP8HaQcLB9QGTQbuBVkFBwVyBPgDjAMSA0YC2gFgAaIAGwCU//H+av7V/UD9nfz6+3P73fog+pj5Eflg+L73RPeh9kL2uvVp9eL0nvQk9ODzt/N08zDzMPMH8/ryFfP68jDzPfOB85zzt/MJ9DH0WvSQ9OL0JfVO9a31/vU09pP2vPZE93r32fc4+L/4LPl9+c75O/rC+nP73/uC/O78kf0m/q7+UP/Y/2wADwGkAR4CswItA6cDPASNBD4FgQXTBT8GngasBv0GXAetB7sHJwhdCHkIygjzCAAJNgltCV8JXwmICXoJiAmICV8JbQlECSkJygivCHkIJwjIB2kHJgfHBiQG7gVLBQcFcgQGBH4D6QJ9AvUBewG9ADYAvf9D/5L+C/52/cb8Pvy2+xT7cfrc+VT5svgP+Hr3DfeT9if2uvVp9Qr1nvSD9CT0+/PS86rznPOP84/zWPOq88Xz0vP780z0kPSr9O/0M/Vp9br1DPZQ9ob25fYo96P39PdT+KT4A/li+c75O/qa+i/7jvvt+4L87vyD/eL9kv7//ob/AACVABwBYAHoAW8C6QJjA6cDIQSNBPoEIwV0BeAFCQZaBp4G1AYmB1wHkgfIB9YHGggnCFAIawh5CIYIlAjKCK8IoQiUCIYIXQhQCBoI4wetB2kHQQfUBk0G+wWdBUsF+gRyBCEEjAM6A6UCKwKxAUUBsAANAK//Gv+u/ib+rP0k/YL8MPyO+yH7cfoS+m/52vhg+AH4evco9+X2ePYZ9tb1kvVc9Vz1/fTv9O/0xvTi9OL04vQz9SX1afWt9eP1DPY09nj2rvYA9zb3lff09zj4l/ja+FT5b/nc+Uj6p/oU+2X70vtM/Kr8JP2e/Sb+kv4M/5T/DQCHAA8BYAEDAn0CswI6A6cDIQRyBMQEBwVmBaoFCQY/Bp4Gngb9BiYHQQeFB6AH8Qf/BycIQgiGCHkIhgiGCIYIeQh5CF0IawhCCDUIGgjjB5IHdwcYB+IGaAY/BsUFgQUwBdEELgTQA1YDBAN9AgMCewHmAJUA5f+v/xr/kv4Y/p79JP2d/Aj8gPsh+5r6Evqm+Tn52vh7+B34vveV9zb3Dfe89qH2ePZC9l32NPZQ9mv2a/Zr9pP2k/bX9vL2Ufd69773D/hg+Hv4zfge+WL5wfk7+kj6wvoh+3P7xPs+/Lj8/Pxo/fD9T/7J/kP/ov8oAMsARQGWAfUBbwIEAzoD6wMuBJsEFQVmBbgFCQZaBp4G4gYLByYHoAfIB+MHNQhdCHkIhgihCNgI8wgACSkJKQkpCUQJGwkpCRsJDgkOCdgIygihCF0IGgjIB6AHXAczB6wGgwYXBp0FSwXfBHIE6wOMAy0DmAI5AtoBNwG9AEMA2P9Q//H+XP7i/Xb9/Pyd/CP8m/sv+936cfoS+qb5ffks+dr4pPh7+EX4OPgd+PT3D/jZ9773D/gd+B34U/hg+LL4zfj1+Cz5Ofmz+c75SPp/+qf6+fpl+4D7+vtZ/IL8Cf1b/eL9NP6u/v/+hv/z/1EAywBFAbEBKwKlAjoDjAMGBGUE7ARLBaoFFwZaBrkG/QZcB6AH4wcMCF0IhgjKCPMIAAk2CTYJXwmICZUJvgm+CQIK2QkPCgIK5wnnCfQJ5wnMCcwJiAl6CTYJGwnlCKEIawjxB8gHdwcmB6wGaAbgBXQFPgXRBDwE3QNWA/cCbwLaAYkBHAGVAAAAov9e/6D+NP7H/UD94fx0/Aj8tvtz++v6wvqM+jv69/nO+ab5YvlH+Sz5LPks+Tn5VPlH+X35i/mm+cH5BfpW+oz6p/rd+i/7V/ub+9/7I/yC/Mb8QP2R/cf9GP6F/uT+UP+i/xsAegDmAGABzAErAsACHwOMA/gDZQTRBDAFuAXuBYMG1AYmB2kHyAcaCFAIawjKCA4JNglfCW0JowmwCfQJ9AkPCh0KKgo4Cm4KRgpuCmEKbgqJClMKUwodCioK9AnZCbAJlQlfCTYJ8wihCIYI8QfIB4UHGAesBj8G4AV0BRUFmwQ8BLQDVgPOAkYC2gFuAeYAbADY/3n///6g/jT+x/1b/fz8nfw+/NL7tvtl+yH7+fq1+qf6Y/pW+i36LfoF+hL6BfpI+jv6O/p/+qf66/r5+i/7Zfup++37I/xn/Mb84fxb/br9/f1B/q7+5P41/6L/GwBsAMsAKgGkAQMCRgLAAi0DmQMGBEoE3wQjBY8F4AVNBrkG7wZcB60H/wcMCIYIvAjlCCkJRAl6CXoJsAn0CQIK5wkPCg8KKgodCjgKRgoqClMKHQo4Ch0KDwoCCvQJowmICYgJNgkOCQAJoQhdCBoI4wegByYH1AZoBhcGnQVZBdEEgAQGBJkDHwOlAjkCvwEqAdgAQwDz/0P/Gv+F/jT+1f12/Rf9uPxn/DD80vub+1f7IfsU+9D6tfqa+oz6Y/pI+oz6jPp/+rX6wvrd+vn6L/tX+4770vsj/D78nfzh/CT9g/26/Sb+d/7W/hr/ef+9/0MAbAD0ADcBpAHMAVQCswL3AmMDwgMhBI0E0QQwBZ0FCQYyBp4G/QZOB6AHyAf/B1AIawiUCLwI5QjzCDYJXwk2CVIJiAmICV8JbQmICXoJegmVCW0JUgl6CW0JXwkpCQ4JAAnlCIYIeQhdCP8H1gegBzMHJge5BnUG+wWqBT4FBwWNBDwE0ANWAxIDmAIrAswBUgH0AIcAGwC9/zX/8f53/ib+8P2D/Rf9/PyP/Fn8Ffz6+7b7jvsv+zz7PPsU+/n6+foU+xT7Ifsh+zz7V/uA+7b7+vsj/Ez8gvzh/Bf9dv2s/Qv+T/6g/v/+a/+9/ygAhwC9APQAbgG/AR4CbwLAAh8DjAPQA0oEqQT6BEsFnQUJBk0GdQbiBhgHQQeSB7sH8QcMCDUIXQiUCK8IoQjKCLwIygjKCPMI5QjlCOUI2AivCMoIlAiUCGsIeQhdCCcIJwj/B7sHkgd3B0EH/Qa5BmgGCQbgBY8FSwXfBJsESgTrA5kDSAPOAn0CHgLoAWABAQHLAF4A8/+v/2v/8f6u/kH+/f3i/ZH9QP1A/eH8xvyC/Gf8dPwj/DD8CPwI/Pr7CPwI/Aj8I/ww/Ez8gvyC/IL8Cf0k/Wj9rP39/Sb+av7W/hr/hv+9/xsAbACiAAEBNwGWAfUBVAKYAvcCVgOZA90DIQRyBNEE+gQjBY8F7gUkBk0GWga5Bu8GMwczB2kHaQeFB8gHrQfWB+MHyAf/B+MHyAfjB7sHoAe7B4UHdwdBByYH7wbUBscGngZ1BhcG+wXgBVkFPgUVBakEZQQ8BMIDcQMSA84CbwIQAvUBiQEcAdgAegANAMr/ef8o/+T+oP5B/gv+1f2D/Vv9Mv38/O78uPy4/HT8WfxM/D78PvxZ/CP8Pvw+/Fn8gvyP/NP8uPzu/ED9dv2R/cf9GP40/pL+yf5Q/2v/r/8AAF4AogDYACoBiQHaAR4CbwKzAvcCOgN+A90DEwRlBIAE3wTRBD4FdAWqBcUF4AUXBloGWgaDBqwGngbHBtQG1Aa5BrkGrAaeBloGaAZNBjIG+wXgBZ0FgQUwBSMF3wS2BEoELgTQA5kDSAPAAmICOQLaAYkBNwHYAF4AAAC9/17/8f6u/k/+8P26/Wj9Cf3G/IL8Pvz6+9/7m/ub+y/7Ifvr+vn66/qa+pr6mvqn+n/6mvpx+oz6wvrr+t36Bvsv+2X7qfvS+xX8dPzG/An9aP2e/Rj+XP6S/v/+UP/K/xsAhwDYAA8BewHMASsCYgKzAh8DOgOMA90DSgRXBHIEqQQHBSMFWQWBBbgFuAXgBQkGCQYkBjIGJAb7BdMFJAaqBaoFdAVZBTAF+gSNBHIEVwTQA7QDcQMEA7MCHgL1AaQBKgHmAF4AGwCG//H+hf5c/sf9aP0X/ar8Wfz6+7b7SvsG+6f6cfog+tz5wflv+Sz56PiX+Hv4KvgP+Ob3o/e+92z3bPdR92z3bPeH93r3o/e+98v3Hfg4+Hv4v/gR+Uf5b/nB+SD6p/rr+lf7tvsw/HT84fxb/br9Jv6g/v/+a//l/zYAlQD0AFIBsQEDAkYCpQL3AlYDjAPdAxMESgSABMQE3wQjBTAFMAVmBVkFgQVmBWYFdAVZBVkFSwUHBfoEtgRlBIAEBgTdA5kDOgMSA7MCVALoAaQBNwH0AF4A8/+9/0P/u/53/uL9kf0X/ar8PvzS+2X7IfvC+nH6EvrB+X35Efm/+Hv4KvjZ97D3Ufc299f2rvZ49l32QvbW9db1rfWE9Z/1hPVp9Z/1d/WS9YT1yPXI9cj1DPYZ9l32ePau9g33bPej9/T3YPiX+AP5i/np+WP60PpK+6n7Ffyd/Pz8dv3i/UH+rv41/5T/8/82AKIAAQFSAb8BEAJGAqUC9wItA4wDjAPQAwYELgRXBGUESgSpBJsEjQSpBHIEmwSABEoELgTrA9ADtAN+A0gDBAPOAooCVAIDAqQBUgH0AKIAUQAAAJT/Gv/W/pL+8P26/Rf90/x0/D78xPtX+yH70Pp/+kj6zvmY+VT5LPno+M34U/g4+PT3o/eH90T3APfX9qH2hvZ49jT2GfYM9v711vX+9eP18fXj9Qz2NPYn9mv2ofau9qH2KPcb94f3vvfm90X4l/ja+Dn5ffn3+Uj6wvpX+9L7Wfy4/CT9uv1B/q7+Gv+U/+X/NgCVAAEBRQG/AegBHgKKAtwC9wJIA3EDmQO0AwYEEwQhBEoEgARyBIAEgARyBGUEVwRKBBME6wO0A6cDVgMSA9wCigJvAhAC2gGJASoBAQHLAGwAGwDl/5T/Q//x/oX+GP79/ZH9W/38/Kr8Wfwj/N/7jvtz+y/76/qn+lb6LfoF+rP5pvli+WL5LPkD+bL4sviJ+G74bvhT+Dj4Afgd+AH4AfgB+AH4HfhT+Cr4e/iX+LL49fg5+Uf5pvmz+RL6VvqM+t36PPuO+9/7MPyd/Pz8Tf39/Rj+u/7//ob/AABsANgAHAGWAfUBRgLAAtwCHwOMA8ID+AMhBI0EjQTRBNEEFQVZBVkFdAWqBaoF0wXFBe4F+wXFBaoFuAWPBY8FWQVLBSMF7ATEBJsESgQhBN0DtAN+A0gDBAPAAn0COQIeArEBbgE3AdgAlQB6AEMA8/+i/3n/Nf8M/6D+kv5P/v391f26/ZH9W/1N/Qn94fy4/I/8dPw+/D78Ffz6+9/70vu2+6n7jvu2+6n7m/u2+6n7xPvt++37Ffww/J38j/y4/NP8JP12/br98P00/mr+yf4a/0P/r/8NAEMAvQABAWAB6AEeAooC6QJIA4wD+AMuBLYE0QRLBVkFqgX7BTIGkQasBtQGJgdOB04Hkge7B9YH/wfxB1AINQhdCF0IlAhrCHkIXQg1CEIIDAgaCOMHyAegB5IHXAcmBxgH7wa5BmgGaAYXBhcGxQV0BTAFIwW2BJsESgQTBNADtANxAzoD9wLOAqUCVAIQAhACzAG/AWABHAEBAdgAvQCVAFEAQwANAMr/ov+G/5T/a/8o/yj///7x/vH+DP///v/+5P7//hr///7//gz/Nf9D/17/hv+G/6//2P8NAFEAXgCHAL0AAQFSAW4BsQHoASsCbwKlAukCOgOZA7QDEwQ8BJsE3wRLBYEF0wX7BT8GPwaeBtQGTgdpB60HyAcMCEIIawihCNgI5QgACRsJGwlSCV8JegmICaMJvgnnCcwJvgnZCaMJlQmICXoJlQltCV8JKQk2CQ4Jygi8CHkIUAhdCCcI8Qe7B2kHQQcYB+8GxwaDBj8GFwbuBbgFjwV0BfoE+gTEBLYESgQhBBME0AO0A3EDVgMEA9wCpQKKAlQCYgJGAtoB9QGxAZYBewGWAWABbgFSAQ8BNwEcAdgAAQEPARwBAQEBARwBRQEcATcBbgFSAXsBewGJAfUBAwIDAkYCOQKYAsAC3AIEA0gDcQOZA8IDBgRXBFcEqQT6BD4FdAWqBeAFFwZoBp4G4gYYByYHhQetB6AH/wc1CHkIeQiUCNgI5QgbCW0JbQmICZUJowmwCb4JzAnZCfQJAgodCg8KKgoCCh0K9AkCCtkJzAmVCYgJeglSCUQJRAkOCeUIrwihCF0IQggaCOMHuwegB04HQQfiBrkGngZoBj8GCQbuBcUFgQU+BTAF+gTfBIAEZQRlBAYE6wOnA34DcQMfAxID9wKzApgCYgJiAisCRgIrAh4CAwL1AcwBzAF7AYkBpAGJAXsBRQFuAUUBUgFgAXsBbgF7AaQBpAGxAb8BzAEDAhACVAIeAmICfQKzArMC6QL3Ah8DSAOMA6cDwgP4AzwESgS2BKkE0QTsBD4FZgWBBbgF4AUJBiQGPwZoBp4GngbHBv0G/QYzB1wHXAetB5IHrQfIB/EH/wcaCNYHDAj/B/EHDAgMCP8H/wfxB+MH/wfjB9YHoAe7B4UHhQczBzMHGAcmB9QGuQaDBmgGFwYyBtMFqgWPBVkFSwXfBOwEqQRyBEoEPAT4A8IDjANWA1YDHwMEA8ACfQJiAkYCHgLoAZYBpAFuAW4BNwEPAfQAvQCwALAAlQCHAGwAXgBDAEMAQwAbAAAAAAAAAA0A8/8NAPP/DQDl/xsAKAA2ADYAQwBeAHoAbACHAL0AywC9ANgAAQEcAUUBYAGJAZYBzAHoAR4COQJ9An0CwALAAtwCSAMSAzoDcQOnA5kDwgMGBC4EVwRKBDwEZQSNBI0E0QTRBN8E3wTfBOwEBwX6BCMFFQUVBRUFFQUwBRUFSwUVBewEFQUVBewE0QTfBNEEqQRyBI0EcgRKBDwEPAT4A+sDwgOMA5kDcQM6AxID3ALcAsACpQKKAlQCHgIDAswB2gGWAW4BRQEqARwB2ACiAL0AegBeAGwAQwA2AAAAvf+v/6L/ef+i/17/Xv81/xr/Gv8o///+5P7x/uT+5P7W/uT+1v6g/qD+rv7J/uT+5P7W/tb+1v7x/v/+Nf81/zX/Q/81/17/ef+U/4b/r//Y/9j/DQANAA0AQwBRAHoAlQCVAKIA9ADYAPQAHAEBASoBNwFFAWABewFgAbEBsQG/AcwB9QHMAcwB6AFGAhACEAIQAh4CHgI5AisCOQIQAjkCOQI5AjkCAwIQAgMC2gEDAvUB9QHMAcwBvwGWAYkBpAFSAXsBNwE3AQEBDwH0ALAAywCVAJUAhwBeAF4AQwAbANj/5f/Y/8r/ov+G/3n/Xv81/zX/Q/8M/wz/yf67/q7+u/6g/oX+kv53/nf+Qf5B/kH+NP4m/jT+NP4Y/v39NP79/Qv+C/4L/gv+8P3w/Qv+Jv4Y/jT+GP4L/hj+NP5B/kH+Qf5P/mr+d/6F/q7+kv6F/sn+u/6u/uT+//7W/v/+DP8o/yj/a/95/1D/hv95/6//ov/K/+X/yv/l/+X/AAANABsADQA2ACgAGwAbAF4AXgA2AGwAbAB6AIcAXgBeAGwAXgBRAGwAbABsAF4AUQBeAEMAUQBDAEMAUQAbABsAQwANABsA8/8AAPP/r//Y/6//yv+U/6//hv9r/3n/UP9e/xr/Xv8o/xr/Gv///vH+8f7J/tb+u/6S/pL+d/53/nf+T/5P/kH+T/5q/jT+NP4Y/ib+GP4Y/hj+C/4Y/v39/f39/dX9GP4Y/gv+C/4L/hj+C/4Y/v39/f0Y/kH+NP5P/kH+Qf5q/oX+av53/nf+kv6S/qD+oP7J/vH+1v7W/v/+//4M/yj/Nf8o/zX/Q/9Q/17/hv95/3n/ov+i/8r/vf+v/9j/vf/Y/+X/5f/z//P/DQDz/w0AAAANAA0AGwAbAA0AAAAoAA0A8/82ACgAGwDz/xsAKAA2ABsA5f/Y/+X/8//z/+X/8//l/6//2P/Y/5T/vf+G/6L/lP+U/2v/hv95/17/UP9D/1D/Nf8a/yj/Gv8M/xr///4a/zX/8f7x/vH+yf7k/sn+5P7J/sn+5P67/rv+u/7J/sn+yf67/tb+rv7J/tb+yf7k/tb+yf7W/uT+yf7x/vH+yf7//v/+DP///ij/Gv8a/yj/Q/81/zX/Q/9Q/17/ef9r/5T/hv95/6L/r/+9/73/vf/l/+X/2P8NAPP/AAAoABsAUQA2ADYAGwBeAEMAXgB6AGwAhwCVAIcAhwCVALAAsAC9ALAAywCiAL0A2ADYALAAvQDYAMsAsADLAMsAvQC9AMsAogCwALAAywCwALAAvQCiALAAhwC9AJUAlQCHAIcAhwCVAGwAegB6AIcAXgBeAHoAXgBeAF4AUQBeACgAGwBDAEMAKABRADYAKAAoACgAGwANAA0AGwAAAAAAGwAbADYANgAbACgADQAAAA0ANgANADYAKAA2AEMAQwBDADYAQwBeAF4AXgB6AGwAegBRAJUAhwCiALAAvQCwALAAywDmAL0A5gDmANgADwEBARwBKgE3AVIBUgF7ASoBYAF7AYkBYAGJAYkBlgGWAb8B2gGWAegBzAG/AegB2gHoAdoB6AH1AdoB9QEQAvUBAwIQAisCAwIDAgMCEAIQAvUBHgIQAhACAwL1ARACKwL1AegB9QEDAgMCAwLoAfUB6AHoAegB6AHMAbEBzAG/AaQBvwG/AbEBsQGWAZYBsQGkAZYBsQGJAXsBewGJAYkBiQFuAYkBbgFuAYkBYAFgAW4BUgFSAVIBiQFgAUUBYAFSAUUBewFgAVIBbgFuAW4BRQFgAXsBYAGkAW4BiQFuAXsBlgGxAZYBpAGWAZYBsQHaAb8BpAHaAb8B9QHoAegB6AH1AQMCHgIQAh4CRgIeAkYCYgJiAlQCbwKKAm8CpQKKAooCpQLAAqUC3ALOAtwCwALpAtwC3ALcAvcC9wL3AvcCEgP3AgQD9wL3AvcCLQMEAwQDLQMSAwQDLQMEAxIDEgP3AvcC9wLpAgQDBAPcAhID9wL3As4C3ALpAtwC3ALAArMCswLcArMCpQKlAs4CwAKlApgCigKKAm8CigKYAn0CbwJiAn0CRgJGAlQCYgJiAn0CYgJGAjkCRgJGAlQCVAJGAmICRgJUAlQCVAJvAkYCRgJvAkYCbwJGAmICYgJ9AooCfQJ9AmICigKKAn0CbwKKApgCpQKzAooCfQLAAs4CswKzAs4CzgKlAs4CwALOAtwCwALcAvcC6QLpAtwCzgIEA/cCEgMSAxIDLQMfAzoDHwM6A2MDHwMtAy0DVgMfAzoDLQNIAzoDVgM6Ay0DSANIAzoDVgNxA1YDSANIA0gDOgNIAzoDOgM6AzoDHwNIAwQDOgMtAy0DEgMEA0gDOgMfAxIDEgMSAwQD6QLcAvcC9wLcAvcC9wLOAtwC6QLAAukC3ALOAsACwALOApgCzgLAArMCpQKYApgCwAKlAqUCpQLOAsACswKKApgCpQKlArMCmAKlApgCswKzAqUCpQKYAsAC3ALpAsACswLOAs4C3ALOAsACzgLpAukC3ALOAgQDwAL3AgQD9wL3AvcCBAP3AukCHwMEAxIDHwMtAy0DLQMfA1YDEgNWA2MDYwNWA0gDSANxA3EDYwN+A34DVgN+A1YDYwNxA2MDfgNWA34DfgOZA5kDcQOZA3EDmQOMA3EDjAOZA4wDjANxA3EDcQOMA3EDcQN+A34DfgNxA3EDcQNjA3EDSANWA3EDOgNjA0gDYwNjA3EDjANxA3EDYwNWAzoDVgM6A2MDSAMtA1YDSANWAzoDEgM6A0gDHwMSA1YDSAMfAy0DEgMfAx8DHwMfAy0DHwMSAx8DLQMEAx8DHwMtAx8DLQMtA0gDLQMfAy0DHwMtAzoDHwNWA0gDLQM6A0gDVgNIA0gDLQNjA34DYwN+A1YDVgNxA3EDfgN+A34DYwN+A3EDcQNjA2MDpwOZA34DYwNxA5kDfgN+A3EDjAOMA3EDpwPQA4wDfgOZA4wDjAOMA3EDfgOMA3EDfgNxA34DjANxA4wDcQNWA4wDfgOMA2MDcQNxA2MDVgNIAzoDcQN+AzoDOgNWA3EDVgNWA1YDSANjA1YDEgNWA1YDHwMtAzoDEgMSAzoDEgMEAzoDOgMEAxIDOgMfAxIDOgNWAx8DEgMtAwQDLQMEAx8DEgMEA/cC9wIfA/cCEgMfAxIDLQMSAxIDHwMtAy0DOgNIAx8DHwMtA0gDLQMSAzoDLQNjA0gDOgNjA1YDSANIA0gDVgNIA3EDSANWA1YDYwNWA1YDVgNjA2MDYwNjA1YDYwNxAzoDSANIAzoDYwNWAzoDVgNIA1YDVgM6AzoDfgMtA0gDLQMtA1YDSAM6A2MDSAM6Ay0DLQMtAy0DLQMtAx8DHwMtAzoDHwM6Ay0DOgMSA/cCBAMSAx8DBAP3AvcCBAP3AgQDBAP3AvcC6QLpAukCEgPcAvcCzgLcAtwC3ALcAsACzgLOAtwCwAKzAtwCswKlAsACzgKYAtwCwAKzAqUCpQKYAqUCwAKzAsACmAKzAn0CmAKYAukCpQKYArMCpQJ9AqUCpQKlAqUCpQKYApgCigKzAn0CigKzAqUCswKKArMCmAKYApgCigKlApgCpQKYAooCigKKAooCpQKlAn0CigKKApgCmAKYAqUCigJ9Am8CfQJvAooCYgJvAooCYgJvAm8CVAJGAlQCVAJGAmICYgJiAisCRgI5AisCOQI5AjkCHgIeAisCAwIDAgMCAwL1AegBAwIeAtoB6AHoAdoBzAHaAaQBvwG/AcwBsQGWAYkBpAGJAZYBiQGkAXsBbgFFAYkBbgFFAWABUgFFAVIBNwFFAUUBKgEPATcBNwEcAQEBHAEBARwBAQEPAQ8BAQHmAAEB2AABAdgA9ADmAPQA5gDLAMsA2ADLAMsAvQCiAL0AsACiAJUAsACVALAAhwCwAKIAogCHAJUAlQB6AIcAogCHAF4AlQB6AGwANgBsAFEAXgBRAEMAUQBRADYAUQBRADYANgA2ACgAKAAoADYAGwAbAA0ADQANAPP/5f/l//P/2P/K/9j/8//K/+X/yv/K/9j/yv+9/5T/r/+U/5T/r/+U/17/ef95/4b/Xv95/2v/Xv9r/zX/Nf81/zX/KP81/zX/KP8a/wz/KP8a/wz/5P4M//H+1v7k/sn+1v7J/q7+oP6g/qD+kv6g/qD+d/5c/mr+av5c/nf+T/5q/jT+XP40/lz+XP5B/ib+Qf40/ib+Jv5P/gv+NP4L/vD98P0m/hj+GP4L/uL9/f39/fD9/f0L/uL9x/0L/uL91f3H/az91f26/cf9x/2s/dX9x/2R/Z79uv2R/az9rP2R/br9rP2s/ZH9kf2R/az9kf1o/ZH9g/2D/Vv9g/1o/Vv9W/1o/U39W/0y/fz8aP1N/U39W/1A/Rf9/Pwk/Rf9F/0J/fz8Cf3h/O78Cf3u/NP8/PzT/Mb8xvzu/Lj8qvyP/I/8j/yP/I/8gvx0/I/8dPxn/Ez8Wfxn/Fn8Pvw+/Fn8PvwV/Aj87fv6+xX8CPzf+9/77fvt++370vu2+8T7qfu2+9L7tvuO+9/7qfup+7b7jvuO+3P7qfuA+477jvtl+6n7gPuO+4D7V/uA+3P7c/tz+2X7gPuA+2X7gPtz+4D7ZftK+2X7c/tl+3P7Zftz+4D7gPtl+2X7jvtl+1f7jvtX+5v7c/tz+2X7c/tl+477jvuO+1f7jvtK+3P7jvtz+3P7ZftK+2X7V/tz+1f7PPtl+zz7V/tX+0r7SvtX+0r7Bvsv+yH7L/sG+xT7IfsG+xT7L/sh+/n6nv3c+SP8V/v5+rb7Z/zS+9L7T/5K+yYHEvrh/Pr7IPo+/HP73/ud/Lb7jvvf+8T7WfyP/MT7CPyp+6n7+vsV/N/70vsV/MT77fsv+zD8SvsU+4D7MPyd/DD8PvzS+6n7gPvf+yP8JP24/J79nfyq/CT9Wfy2+3T8dPwy/YL8Z/w+/Gj9g/1c/uX/4v3l/4X+nv1P/gv+oP5P/tX9Qf5c/tX9d/6F/uT+2P/l/wAADQBc/qz9GP6g/r3/GwCU/6L/vf/K/0MANgBRAHn/UP8oAPP/NgBDAOX/yv/K/0MAvQCVAJUAsADLABwBbgH0ACgAd/7W/pT/ywBgAfUBEAKJAYkBRQHoAXsBvwEDAmABKwLaAXsBiQHmAF4ADQCVAFIBAQGxAdoB6AHMAUYCEALaAZYBYAEQAokB6AEQAnsBNwEoAJUAogBgASsC6QKYAi0DigLAAkYCRgKlAooCBANjA6cDYwOZA90DSgTuBf0GQQfWB8gHhQdpB7kGrAYaCOIG5wlfCVIJXwlSCW0J2AihCB0KNgmVCeUI5Qi+CSkJzAksC1ULzwuLC30L+QyrDvIQKBHkELgOLw1iCzgKGwm8CIYIDAjWB7sHTgeDBoMGngaqBY8FBgSKAkMA//4y/dL7SPqX+Gv2FvT48dvwlu//7U/tW+xn6xbrJexg70nyGPWX+N36kf3l/3EDtgTFBWgGGAfxBxoIJgcwBWMDbwJ6ALAAlQBgAbMCLgS5BrsHUglVCxQNgQ0WDggO4Q7GDsQNfwzZCdQGxATOAnoA8//J/lz+GwAbAKIAmAKZA3QFkgc4CmQMaQ+HEecS6ROKE2MUExW2FYAVqBUwFrcWJBfiF54XnhczGIQYQhnLGokbixwGHqkewh2MHdwc9hvoG74aGxoZGeIXjxanFBwS/A6YC/MIdQZ+A2wA8P0g+vH1BfLy7SLq9OYk4+vgEN9D3cjb4dpm2X3XONY41r3dPOFV6MDw4/U+/DkCGwkxDnkRIRVcGH0c0h5nH6keVBxdGQQUiBIKD4EN0AwWDjEOIg3rDD0NIg0SDFMKKQkOCQwIoAdLBTcB7fvK9sPyee6r6xLpmukU6nPqF+z/7SHyxfNT+BX82ADiBvcLoBAeEy0UbxPpE/USKBHjD/wOdQ75DJoMwAoOCYUHrAZOB9YH8wgsC+0N/A4yD98NFA0DC2EK8wj/B7sHXQgdCqQKJQ9DEUYTkhjoG+EflyROKXorEi4ELgEs8SlLJzcjmx4qG6oWKxM1ET4OiQo1CPsFLgQeAioBNf8k/XH6rvYE8XPqMuO62ybTn8oaw4e7cLVdsXOusKoOqmWukrnlw+7RBuFB7SP8lwokFykjoiueMS43XTu9PAo6NzTfLzwmBh4KGDURtAssC5UJDgmtB0EHQQd5CBsJuQbFBSEE9QF2/aP3e++U5RfbdtLwyofDFL9vvSy9b71owS7H2s2L18Th4es4+HQFoBApGr0iIierKGwrvyzjKdInSCXiIOocXBh8E/sNHQqUCFoG+wXIB/EHUgnNCtkJUAj7BTAFVgOWAdoB9ADY/xr/lP8o/70ASgStB0cLlBHFFiobGSGlJCwlmSWNJkkmlyRtI3YgUxuEGOkTZQ3/B4kBnfxF+Fr0RvDf6qHls9+12OvPz8bcvR+1mKx1pyujB51DmCSWZJwqogOsoboux9jUr+VR90IIDBl3IbMtzzZGPmhCC0P7QZg+iza5MQ8sWyAPG8UWKhIjDnoJJgf6BLQDvwFe/0z8IPqf9Tzyr+7X5cvdlNSizOTCh7sGtkWzjq6crtWwHbSju/HCy8xH11rjs/B5/88L4BYIH90lpi2qMFwyajJmMJgtkimyJMYfXBjYEfsNeQhLBZYBvf/x/k39F/1K+875v/h69zb3D/jy9r73Hvn1+Ov67vzl/5sEXwkUDUYTNRmnHa4hESUwJ/kmFigWKGQmASM+H18ajRXwDwAJfQKC/PL2wvFo7Mvm3eBa2v/Tlcxew625CrAYqGmfGpiMk/mLyocui5uU0JxTqwC7jcfb1ofuoP40EOQhBC5KOG5GQUy6S/5L6ke0P5o37jARJWAbPRbTDhsJogBI+tn37vMH8y7yh+407bvt6+mV5rbhxtpX0K3KHMSXvMO2ErVqsdCturCUsuC3uMAMyw7VFuNX8noAZw5uG8AkyysbNJ05eDuTO0w5ozS1Lpomwh32E1MKOgPf+0L2VfGu7YLrZepW6YvoA+hw6KnqPusN7qfx3vLi9L/49/l2/R8D7wY+DvoVzRvYIuMp+C65MeUzLDbbNWE1lTSbL5MqfCQ5HMAT9Al6AAP5OvG36uPkKt5z2dbTYM0Tx9K/kLjTr3eoDaE1mG6RxYyFhjuCAYCXibiVe6Jmt3XJLNcr8HcH8hm2LxI/kUt/WZBkpWkiY9heiVcCRpE6FTCTGdcQkgeb+y7yeubA34TbBdj52OjWhtQi2YHZMdqZ11zT9MymxqzBmr7gt5m1S7eIs0i1Crn3vTrG4NEr30/tPvzjD9MfYi3GOZtAvkVASw1Nxkp6RYk9UjSDKDgb3gzu/PbwOOeJ3knYd9Mw0WbR/NH/05XVA9de3Zzipugd8JD0SPrl/3ED/wd/DIgSMxhnHxQnEC1DM/46bz7rP6xCZkFmQexART21N2YwnCepHpQRaAYF+svuvuZh36XWVs9MyZTDjL4KuXy0+q42qnSmbKGXmuyUlZBajS6LIItJi72Q66TbtNvFmeBJ8h8D/B/ZNPNEsletZeJt4XWHeLFwBWKmWOhGjzCTIUAPmPnb8O/jZNjly8rDusH5voLAHMSlxZ7Jfs8+0U7Tcc8tz2nKwsb1xIjEC8Lzw3LH3cZryz/SD95w6Hr3kgeBFi4m+zhcQzJLZlKqUpxSBlHtSRI/lDOXJFcVwAIF8ozgQdPGybrB6Lw4vJW7jr/AxRjK+tAH2SHhFuuS9ST9+gQ9DS4VrRidH94mzSxSNFE84EGLR2lLHE6/Tg1NjknxQys+xDjrLh0kvBlKDTkCofZo7DLj/Nro1lzTY896zDHJE8dSxN+/Hbyqt6+yLq1mpp2eCZbZkMiOjowxjRyRx5berR3FHdZY89sKvhrsNzlPoF1LbKx2Unm/eax2s2nRUfpA9y2uEFD/HO8O1c7OzcV7vKu4UrN0t7+8asLZzNPRBdjd4GXhr+X44IfdI9qe0h/P2s37yJLKEM6kzdbTyNvr6Xr3yAcMGZ4oOjaaSFVQ41TmVrZRJkxfRbc4GSpCGU0G1PRZ4gzUXsNpucC0hbGjs+O5973sx+LSadtt5jrxjPqnA1YMexIwFg0akSD8H1IjJyp7LLsyQjtiPlBEWElNS/9MeEy3SblCQzzoNVsp2hvkEJUAP/Q+6wPfpdb60MvM18sozDbMX8yWzX7PmM71zb3MgskdxXG+frXqrH2jt51wm7GZepmanAOjFrjozSvfs/mxElAisDx0UuVe6WlEcFJw+mucY/FUQzx3Kd4V9/l65tDYvcMPvKq39bNgswK0fb3qxqXOW9uD4+rof/Jy8lz1cPGR7HrmAd7D2BvVY88tz2jSTdJy2KjhSPHH/akN+R2yLMQ4EUfmTW9Pr02kRm8+2DNwJdsTLQPa7yvfBM9ew+C3y7LHsF6yd7kYwkLL7NiI5mHwdv1ECUMRyBiRIHkiwCRVJdEmmibqJSQokyoDLU8yVTbGOW8+jD/fQPg/Nz2NN50wGCnhH/8QJAY7+lDuhOSg3MzVuNFjz9DPj9Gs0r3UYdZy2HLYfddS1fDSN806xqS89bN8q4ykA6MnoP6fOaOsp065TdKK3wX6bxNgI8Y5OU/fWjpheGYZZq9eG1buSuwvwh33C+nwQtwk0mW/qreMtQa2WrgMun7G68/313fkuOtJ8hL6svhA/fL2BPGQ61fhF9vo1jLSFdGG1BPYD96V5r/4BgTmEUMici8XOg9G1UslS+hGpD0nM8MmFheqBWj0FuMM1B/Gwb0ttYeyb7S3tybC2s2N2Djn1vVeABELIRXcHKwg3iaQKKsotyfsJmQmYyV+JWYn1CgeLbkxKzUKOqE7bDzGOaU1/DD+KZ8gTRdiC1D/4vQW65vhuNpe1O7RI9Ek0nrV6tfh2kXesd713sze79ou2ILR78lMwKi2Fq93qLSk6aN7osSlsqsVwGHWD+eYAp4XUiNgPWBO11UsYWRikVxgV9pOVD4gJtsTkv535EbW5sxEu065ULokuDu+88PZzAfZZeHy7Z709/mVADX/5P4s+RDwVulh38TZVthq04bUndq83OPkcPF6AJoMixwAK241E0DeSLdJy0WKPvwwVSWeFzMHGfZt5lLVP8lxvrm4VbUTtgC7vcMh0L3dxOp7+O4FdQ79F7gfAiRXJkApTikiJzgkOCT9IKsfFijIKaIrlzWBOLk5BkBxPw083jeeMbkoxB7uFl0IRfix79bk4NnB1+TTndHz1D3Z890W40Xnqep27DTt+uqk5xjkutsw0ZrHM7nrrVelQJ/tnbie5KCDpy62TdKQ43P7uxhmJwo6PVLGWz9kW2WyYCxYjkm9PL4j0AwU+6zjHs62x+a7z7WSufW8KMOuy77VeuYQ8Jj5swIHBTYJuQYhBKD+BfIS6dvfUtU11AbQVs841grbXeUE8RIDmRQZIRcxiT0LQ8dLoEw6R0Y+Ly8XIK4Qov9Q7pPc985Dw9a5Frh0t5O6NcMczT7aLen09+wENxIsHDQhSSYMKoMoxijRJm0juiB/HWQdgB5QIiQoHi2vMwo6Kz51QndDWUENPIYzGSoxHysT7ATX9iLqK98u2K3TaNIL023V19yP4sPp9vBo9JX3o/e59OnwIuoi4nzWxslHvXSvmaTyoLWcIJzYof2nSLWx1T3qDP/uHwYvbT0DWHxgFmQNZ/Zg5VUDRxY57h+bBNLzpd/dxhzE2buZtSC+5cPwyg7V998Q8Pn6IQQgDNINJhDDDE4H2AA58MrlHN4k0oLRm9Bl0BPYfuAK7G745wmzHHcpgTjlRHFIUk4oTbxEtziaJlkW7gWD9AzlRNWOyPq/rbm7uUe95MLazWnbjOks+YYIsxNzHnAljifxKV0qTilyJocigyACG1oXNhosHDIgJyruMKk4PkFERahIVkh5RHk8yTLtJ4gaLw2U/1TwxeKc2fHTqdBa0onWW9t45Sju1PTi/eYANwGJAXT84vQX7I/ioNPMxDG4rKdmnX6b1pd8mqSiX6p7vPPdxvQuDHorqzncR4hfX2eHZwxmC10BTrE9Vi5jFJj5Sel81hrDkcHcvfK6pcXpzn3XJuS97jL9hQdzDaQSlBH+D9kJegDa+H3oydxh1l/M6M0h0GjSzN6n6Rv3/QZBGCgrYjbHQk1LhEu9TRJIJzssLTMYxQXK9kTmBdityrvCb70qvIXCc8hZ0czen+wG+4gJdBb6HhEl1CjSJ+olBCW7IYwdABqfGDwVWhcFHVsg0SZILlM1+D8dRqlJTUvNRj5BpjaiK/oe1Q/aATP1wejO37fZ59Vw1+/azN7L5nvv9PdD/9EECweNBBwBtvuL8bDmc9mryR28Fq9vo1acl5rcm4KeaKcossnCNuaO+7ES8DG9PApL9V/qYTph01t0UuNDGzQ9J6kNXPWy5yvWOsZHxm/FvcPpzhbaBuF47QD3vf+GCIsLcQyXChgHbgEN97HvLuGj1eLSDcx9zojVZ9od51z1PARtEhkhyTKfOo9BFEl8RlBElj0hL6kebQnB+T7rk9wm0wjJXsM3xGPGlcwb1VLe+emh9jwEQRCvGfwfNyNtI9YhCB+LHA0aWRaMFM8UZhaXG28klSt3Mu854EFHRyVLukukRlY/KzWqJ/IZ9goh+/7s+uGB2djUXNNV1xvdaeSu7fH1r/9dCOoLdQ5WDD4Fj/x+8RbjatN5wx20MKYsm9GUPJQMmFiddKbzshzEeubAAjMYAjXXRJNMNV4uYp5c4lMGSQc4WCemHE0GQe0f4LnSe8R8xavJ1cr01QrkaOwB+OYACQZWDM8LDgkuBAz/KvjH7PHkZNhdyzPKLsfGyaPVot2R7Gj9Ig2LHEwoFDgEP0pAG0VlQOE5azPkIaAQFfze6UXe8NI2zM/GzMSryYrOmdci4nPqhPXY/4kKpROjGvkdphzXGQYVQA8jDrUMmAuBDQsQ+hV/HRYohTKdORZCw0jYTelP9U4RR+M6SC6aHS4Mkf1e7lfh+dh30xfSJtOp2ariWOpO9cf94gYlD/8QyxFxDLEBUPYq5+rXE8d0t76qZp2plHuRO5MCmuei8LDavGDN3fEdCgUdCztfRR5HsFYRWF5NX0UzOgUmjxbhDmP61+XL3VzTf8dfzJ7S1tPr4Mnt0vO6/ZkD4AVGCgkGYAGM+pzzhOy24ULckdKOyNXKM8pIz3ndKudQ9gsH+BRPIYcrfzfVOnU5dTk/MZ8pQSFREcwBRvCl3+rXCNFFzYfMfc5q0zLbd+Qc7071av5aBkcLlBHRFSEV2xNdEDsM/wf9BgAJoQh/DEgUVBxYJ5Iy5DuFQ4tH40tRTRZKAEXGOdkrWB7fDUD9r+7s4dDYr9St02HWKN3z5aXwVvotA+cJ4Q5SEvIQfQtIA5/1sOYg2FXGgLZCqcOcFJQNkMGSHZqWomiw3L1pygPoPwbxGFwyu0PZRStP71NFTiRCBTf9KDAWEgyxASjumN/v2iTSh8wD1zTcOd//7Yb2I/ylAtADuQZ7AT78DfeR7IvoZeF/2MzV18vXy7XP8NKM4PzrYvlTCmgXwCSyLCk0uTnNNRoz9Cv/IVEaSQxq/rHvHt9k2E7TPNDu0RrUqdk+4gjrJPSO+78BdQYsC44NJhBqEAgOOgtOBzwE7ASqBV8Jtw1VFOsdjicRNi5Ay0VSTntO/0z/TMhDFjkBLNwcZQ00/n7xu+Sf21bYH9eC2qjhgOpp9b3/bQkXD28TSRVtEhQNSAOG9tvnLtjFyLe31qidnraUbpE8lI2cMqfbtALF3c+e44MGYxTvKFpCaEICRnBQuEp+P4g0XSoGFUQJPwaD9HDo1uQb3VPWQ90Y5O/jYO8d+GP6VALaARACQwAA93DxgOom5AbhPdm42qHUxdHg2Q3dAOZM9JH93gzlGaYlzSzFMAQ2MjENK9EmUxthEzgK4v1m813lN9642ovXjtk03C7hz+jM76T4Q/+zAloGQgh5CGEKAwuwCfEHFwZjAy4EbQneDCgR9Bp8JKcu6T5KSVRPklTGU1RPJky7Q4s2MSgZGa8IPPva72jjuNre2HPZ892m6LbyWfxrCE8QVxWSGP0X+BS3DaUCXfbL5sDWR8bOtGinEZvElN2T8JZDoVmvRLtdy/TVBuoCCmsZlSv7Qa1DcUgQT/lIbT2bL3wkKhLjB/sF8vb866fprOOH3azjuOtz6gfz/f3//j4F+gTAAnn/4PNB7V/mSODM3qjYW9sT2FPW298K5CjuZ/xXBPYToCFsK1sxhjPNNYwumiZqIdEVjg0wBUj6wPAn5RLgpN4b3VTfrOOM6ZnxzvnmACMF1gfKCKEIdweGCEII3wQJBu4FIQTMCTIPKxMpGnAluDBOOupHBFDRUYZVPFFzSf9DFDhCKvccrA9iAvH1De7z5TzhquIp5snte/grApoM+hWjGqYcshvTFu8OSwXo+OHrk9xHzj7A/7GQpzSgqZ0Xn7OjCrD0uyLILNex3vPu0Ax3GI4nWzqFO1Q+M0NIPzo2hirMI0sWgQ2ODVIBvvfI9aPvp+kl7LPw5u6D9ND6jvuG/538ffls98ntfeig5Ejg7OE532bi0+KN4cTqzO8N990DzQqPFv8hkCgeLaQswS0xKJ8gfBuiERELZgVn/Mj1Jewd51Hm4+Sj5prpk+3g8x75lP/oAZgCSgSnA28CqQR1BloG2Ah9C98N8xH7FrMcRCPXKqs5S0FJSHJRxVKYT4VMQkS6OgYvbyTuFkcLRgLm96PvPepV6JjorOyt9U39JgfVD90U8hknGQQUxw/gBWX7ivBN4wLWxciavuayGqkTpeeiEqRzrky45cMG0Bbax+Oz+VgNYBv0K8A14DhLQY1AHD1fNCUpTB9yFfAPhgjx/iz5nPO77YLrT+1P7QLwQPWf9RX8j/z1+ND6dPMX7BHoMuMH4rTgIeEz5Ljifeh57o/zyf7gBZwN2RpeIoMo2SuKLQwqVCT5HRMVLgyDBhj+vveX8JrpAueV5qPml+cj60XvuvVX+5UAcQPEBPgD+APOAqcDZQQyBsoItAugEDAWzRvlIiosGzSxPVVHEE9mUnRSHE5uRnk8qjAOI0sWRgp3/oT1r+7e6VXoRedM643ygPsVBWcOtxZgGwMcUxtIFEYK2P8V8wDmVdcMy+7AirRwrFqnb6M+pn2scLW4wKTNE9g33qvr4ga7EDkcZS/FMNUx/ztJN/wwPyifIEsWkQ9bD6oFMv2a+kz0N+8O72PxHfDA8JP2Qvb3+QP5xvRA9XbsQuUa5XHgFeIh4e7ileah5azsj/Md+IoCdwfjD3wb/B/PJVcmiyVDIpcbjRXTDkEHVALC+tf2HO9W6Y7q6+my5z7r1u0R8V32gPtc/ob/yv9RAK//KP/OAkgDPgX2Cl0QHxRFGxwjKiziMf87A0eTTElR1FNsTQNHsT3wMYgjMBZuCkD9f/Lk7WTp2eaj5rXpOfBu+M4C3w2ZFPEYfBtRGhIUbgo1/x/xCePK1LfIZL5+tXyrIaWHoWKju6hgs1i/XcuJ1mHfh+5GCg4S9hvEL5sv7C80O+w3Vy/tJ6wgpRMgDMMMsACw90L2cPHu68vuV/Ia7vXvafXe8qT4ofao8jT2Tew15UTmVeBV4CvfPuIn5U7kUO4/9Cz5+wVECYQPiRtlHmsi2yR+Jfwf4xilE94MpwOe/a72H/FM60foz+iM6SLqq+u97hPyhvb5+mj9DQA2AE/+UQDYAM4CmQP7BcAK4Q46FFkfDCpcMrk5M0OCSjdOmVCWTolGmD6GMxMmRBoxDl7/qvOE7JfnbebN50DsSPF7+H0CqAzqFDUZQhmvGXwTbgroAU71eOUD14LJmr4rtFatXKgwplqnsKoQtPq/4ckC1gHe/eMJ/YENzBJ+JbUuTCj8MLI1YCwrJA0igRbqCz4OKQnH/YD7AfhU8Hjti/FF7xfsS/N+8RXz1vWj70bwGu5c5MXinOLP4IDhG+be6SDpy+7X9lP4YAFSCbIKwBOXGxIdFB5PIc4cMBZ5EdsK3QOv/6b54/V88Mbrjuqd6z7rjurV7Dnw+vKH9zz7I/z8/Bf9JP13/rAAwALUBlgNTxByFYIfgSfkMtg8g0K3SYhOH1BeTXFISD+CMLIkrRgDCw0AafUm7cvmeubq6BfsB/NH+UYCmgwSFMoZOBvxGPYTDwrK/1r0DOVH19TJ0L5VtcOtKapZplmmEazptP3B2s0f12PgoOQh+00P2hL1I1YuqygJMUQ0ASyII1kfthUPCrUMNQiP/Iz6UPal8KDt9e/1753rV/If8T3zb/np8Enyz/HX5XjloOQ+4tTjDOXG68TqiO84+Jf4bACjCQ8KpRO8Geoc9xwvHqYc7BWrDogJHgJq/qT4M/UR8eHrdOsl7OLsTex57mPxFvS+9yP8F/3k/lv9C/41/xwBPwayCj4OwhRTG2Yn/TEbPIVDskYLTB1PXk1zSTBBXzQiJ74axg6lAg33/uxw6Hrms+j/7YT1j/zQAxQNPBVEGi0dRBq0FN4MvwGS9WTpjtlPy1i/+LWcrgKrGqlrqYyt7rdbwVPNt9lv3xrluv2BDWASfCRTLCInajJfNNkrZCYZIT0WkQ/vDr4Jr/8U+/L2H/Hy7ZTu/uyc6pTuve5/8if2b/C08aXw6Ocg6X3o5eWm6BLpru2z8GbzmPlZ/A8BDgncC3wT8hm/G6Ycjh6kG0EYrhCjCS4EQf7a+JX3s/C67HTrjuqC67rsNO3L7kvza/ZW+v39Gv9c/l4AiQGNBLwInQ6WEjMYriH1LA40fT4pRdtGq0p5TTFKU0YDPoUywiX0GpEPHwM4+CvwF+xz6jTtjfKy+F7/Jgf7Dd4VUBlRGgwZNxJ8CugB1vXE6ibcBtCKxZW73bUosjGvQLB7s3u8csc+0VbYUt5p5F/3eQgKD9UgWykgJuQy9DT4Lv0oayJrGZMQbBEuDIcAW/2u9h3wx+x47dPrfejm7ivwdPMG+6P39fiH9w7vlO5q7X/pq+sU6mzur+488m74YvnW/qoFDAgcEp8YfRxMH70iqx+yG/oVWQ5aBuYAtfqG9i3xx+wW6/npqeoj6xfsy+7e8ij3/Pxr/6cDVwTfBCYHYgtlDa4QnheRIAopADRSPddEWEkXS1tLdEo4Rpg+EDWSKcQecBS7B538aPT/7YLrTeyb8kX4DQDlCEEQIRWhGeYaJRheEb4JHAG89vrq9d780SzGbLthtDGv0K0Wr1KzZL6eyWrTYN6t5EXv+ANPEGIckyoUL7gw/Dl/N4IwcydlHtoSVgzKCMwBVvoY9ZfwNO127EDsq+u67LPwmfFj+j78BfqR/Yf3EfH28Gjsc+rT64Tsve5w8RH5JP1eACcIzQqED4QYLBwjH8cg4iCmHEIZ1xDxB4kBmPmc84rwJew96krqq+uu7aDtm/LS88r2CPyHAEUBFQWDBmgGrQeXCpoMORO8GfMipy4IOSZDoExjUC5RYU81TUFDdjrhMA0iMBZHC5T/d/W77d/qjOmE7Bj1WfzHBskQ4hcvHu4fcx5dGXgQrQdM/PbwQuUH2c3NDcN4uva0T7GEsPKxg7gaw9nM79q75AXp4v2WEvsW+ycnM44vrzP8Odgz4ylUJCUYHQoaCH4Dwfla9IvxUO496ojvLfGu7e/0+/Oj92r+R/nE+yP8w/Jh8KPv0+v+7DLs2u/b8Ib2F/3aAa0HnQ7HD2YWWB5nH6keuyGaHf4YbxOmCzoDI/xO9Vfy8u2C6zHr/Ot57unwS/NO9Yn4Y/qF/mv/ewFlBGUEFwZHCxIMDRFrGb4jASzANTBBtUjYTRVSzk+fSxtFnzrEL/UjMxhJDNgAYPgF8g7v2O5j8V/3XP6UCHkRKRqdH8oiyiKMHX4UwQtQ/xPylOWB2ebMrsJgvNG2ybEosuezxbf/wuvPVtjE4QbqFfz/EIMXwyZcMiAuAjW6Oog0by0sJTgbWw/oCpIH7vwz9R/xNe636kDsYfBN7LHv+/PW9Vv9Y/r5+tX9TPS08Vjzbe8p7xzvz/GB8wD3hf7cAkEHtQzHD8MVLR24HwYejx8IHycZ9hMUDWYFxvwM9oHzlu8j65DruOvW7UbwE/LI9Yn4ffmR/bAAAwL4A3UGuQbnCQoPDhJCGfYkzSx6NMVBZ0psTWRRqFHVS+VERT3uMNskaxn7Dc4CSPox9BDw5u6N8rz2yf7/B+8Ogxf3HMQe7h9gG20Svgle/6rzYuhg3qzSZsgXwQ27ZrdYt9K33r6Nx+DR8NvU42Tpg/2rDmMUziRBMqYtpTWxPfQ09SxLJ3wbkA6ODe8Gb/nI9Trxxusl7LvtT+3u6x3w7PI29/D9PPv8/A0AyvaD9AH46fCX8BPyWvRL83/6ywDQAzYJFw9pD00XIB3CHfccmx4eHFoXHhNxDC4EgvyG9vryzvCC6zLsu+177xHxxvTm9+j4p/rl/zYAVAL7Be8GUgk9DUEQwhS/Gy4mIC5VNjJCSUhRTcBPHU8jSoFB3jeJLJ0f+BS+CRwB9fhY80nySfIM9u37EgM7DKUTYhyvIogjiCPCHSsTvAi4/A7vIuI614fMJsKYvQq5trbut9a5j8CwzAXYnuOC6+zyFwbmEdkarSnBLQEs4jGGM1cvgyjlImQV+QyaDPoE4v1i+Uz0OfAo7pvyivDW7Znxs/D99Dj4APea+tr4PPI/9OzyVfHs8nX0/vUo9/D9swKSB8MMnw9BEMMVyxoPG6EZzRs/F4wUQRDqCyEE4fwB+Nb1zvBF72Dv8+7A8Pryg/ST9h34v/gv+/z8ef8EA/sFyggKD+QQnhdoIHUoMDD7ODJCqEhqTGNQC0zZRcw9GjNYJ/Yb5BDTBZ79e/ir9ODzJfUB+O780APqC6QSJxktHcQewh3+GGkP1AZU+Xbs6+BG1jTLAcQwwES7krmyvGS+K8VFzbTXy93x5H7xMAV4EEgdhCnBLcQvHzYONGItOiWaHSoSbgpfCeYA8vaZ8dXss+j56ZDrn+xc7cLxn/Xu/P/+Nf/W/ln8/fQl9T3zpfAR8QTxIfKE9Zv7DP9IA8gHzQreDI0Vkxl6GlEaoxqcFs4TZAxOB7r9eve28m/w/+1c7U/tDu+l8BXzufSH9wP56fkJ/Xf+lQAhBGgGlAiMDDIPSRXQHXImsy2pOEpAHkfHS5NMcUieQj04lixqIYEWzQq/AdD6JfXe8mbzd/XB+V7/8QcXD48WcR0+H/0gVBz2Ew8KW/3m7sXiK9ZRzBrDIL7juSK3qrdCuju+WMhvzpDaWuNW6X/6Fg6zE3chsiwqLOktfjbTMH8mlCLmGgUMYQppB7j8MPOK8Ars8+Vk6XPq2+ft6lztfPAq+Cj3o/dv+cb0EfEi8zzy6fCL8f30JPTB+cr/fQJ0BegKfQsWDgcWuRd0FrcWZhaHEdMOlAjpAvf5MfTM79btL+q36n/pkOte7hDwBfK69TP1y/eL+cb8hwB+A00GLAv7Db0RHRttI9cqajLIOiJBskaaSOpHj0GpOEgu2CKrF3MNbwIg+nX0OvGK8Lby1/Yh+8sAhghBEMUWsBotHeYaSRUGDbMCKPfD6bzcoNNAyk3B6r1FvJ+58bkevVzCB8ju0ZDaBOD56eL9RAkrEykjWijvKFcvCTGhKlAi6BtSEjUIZgUoAF/3EfG67Kfpi+jN597pO+ky7K7tnvSk+Cj36Pg4+LTxRvCX8Bru5O2v7mPxtPER+YP9iQF0BeMHXwl1DuYRSRWKEx8UARLwDx4LFwa9/6P3cPGI76vr7eo96ljqXO2F7R3ww/Lu8xb0hvZF+GX7F/2WAesDKQlZDvUSIB3RJiwtZDezPqFEz0cSSPNEKDyhM5AoyxqUEWgG0/zy9s/xEfHO8An0ifhn/LQDAgrGDoAVLhWbFb0RHQqxAZP2TOuK3xvV6M2jxHTAKrxpuSm72rx5w9fLrdPL3V3lMev3+RsJahB6GoslwyYlKcUwzSxGJNAdwxWjCYwDGwB691Lvkeyz6Hrm6OcR6HjliefB6CPrmfGe9NT0y/d49iT0n/Vo9EvzSfIJ9Mb0Hfig/pgC0QQdCugKwwyTEDcSJhAlDzEORwvYCBUFGwAF+uDz2u/w7PnpFOo56PnpoO3Y7uzyUfcZ9ir4f/rE+wv+zgJ0BZQIWQ46FEccqCbpLdk0MTktPyRCTUJ0QWk6PzE9J3AcKxNtCfP/Hfj68hPyqPKu9nT8ogCRBiINEBMkF4QY4hd5EWEKYgK89vDsm+E31SjM2cSPwEe9ibx7vDy/9sVRzA/WRd6M4DbmVfEhBOUIMBayJL4jCilTNZExHCyiIlQc7Q3UBlwHjvtY89btYugC59bky+Yd5z/jHugI63X0l/gS+pT/f/pp9en5ufTF89vwivB88I/zxvy9AI0EvgnbCvkMAhPeFXAUEBP2E0EQ7Q18Ck0GCf0z9ZbvT+3o5/bnYujQ6TLsfPDI9R75s/lK+5v7kf0M/+kCZgXKCI4N8hDXGVQkqyjiMZA52DygQ81GOEbuQbk5qS/KIpIY0AyiAIv5i/G97sDw0vN/+rAAMwepDekTrxkqG2AbGRk0EHkI5P7D8m7nn9s+0e3IDcMVwNC+PsCswQXHzs5u1pbehOTq6OLsd/7lCJ8PWB6XJH4lBi/lM34uPSfHIKoW2Qn0CQcFf/ri9Jfwx+zE6t7pWes25n3ocek58F32Efm4/BsAwflW+pv7G/e89gn0JfXg80j6UgGBBQsH0Aw7DPwO6RM8FTkTiBIBEuYRFA0FDNMFQf409ljz5u4x6wjrCuzV7IrwxvQD+e37Y/rh/NP8JP0cATAFaQemCyoSUBlcIbMt/zIHOB4+g0KGRHpFTkP/Oxcxnih/HZgTsAnx/m74j/M983r3j/xiAvMI0w7DFcoZFB4UHnoatBT5DEgDf/oQ8ITkjtkk0q3KisVGxZfFUMP4xm7NNdRO2z/j6ugq553rGwCbBMELIx80IUYkWzG+NPEyQyuaJgAa3w1pD6kEFfzx9YfueO0K7D7rXu4g6cbrxOo/9CH7LPkqAaQB6Pgm/kr7NvfW9X7xtPEQ8Cr4DP8cASoKgQ0jDvoVaxmTGbkXgxd+FLES/A6oDLgFQ/8A97n0zO+67JHsW+xQ7n7xGfYI/Fv9Jv7Y/4X+rv4BATcBBAMMCNAMcBS2HicqXjMLO+BBBUjrSMRJ6kdXQHw1YCygId4VsgqYAtD6/fSB8672c/scAaEIug8JF6QbdB9BIQYeMRc0ENEEVvra74Pj0tm40arItMa+xPXEAsUHyBzNodQy27njOeho7G3vdv1fCSUPRRtDIswjDyzsL+wvqyh5Is0bWQ4xDh0KogDr+pL12/Cj73bstPHE6p3rrOx88Mr2VPlM/Ib/bPce+Sz54/Wh9qrzFvRo9M75HAF0BVMKqw7tDYgSZBUWF0gUmRRgEjQQZAxkDBcGKAB9+bz2Y/Ft71Lvve5g7zzyd/Wm+dL7dPz8/Ff7I/wk/WABpQJdCGcO9hO1HbwqnTDQN5g+C0MmQ4lG80RvPhA1mC2TIYYZTxAmBzYAVvp7+Pf5Q/88BEQJ4w8uFbkX3Bw7HfIZIhaCDt0DZ/z68h7oe95i1/XN7cjqxqbGo8QRxpDJs87x013cJOOh5YnnB/PYAGgGSBRcIf8hxiigMuQyUyx1KBoiohGpDdwLOQK2+9f23vId8JHsLfFc7bjrhOzk7YT1UfcF+g8B0Po4+LP5kvVa9Nvw9e9s7gTxb/ni/WYFfQsFDOYRchU/F/sWPBWlE/8QkA6LCxoIpwOp++X2P/SH7nbsx+zi7Lvti/FQ9hL6Vvrh/O37Svu1+hX8x/03ATMHZQ2AFdUg1yrJMp05jUCeQu9C1kPRQAg5aDG5KGUetBQSDHIEF/0q+A33mPnw/ToDAgqFEIAVXRm/Gywc/hjAE6YLOQKY+WDv1+Xm3XnUic2qyOnF9cQCxcDFS8ikzf/T79oT4aDkP+P28EP/OQJgEjgbWB7SJyQxlDOWLGYnhSGHEfIQLAsqAXP7JPTA8PXvrOwE8bXp7uup6tXsGPVC9jn5DP9R90X4AfgV81jzru2u7c/oDu9A9Tv6HgJ5CFIJ8A/CFBgYPRZZFtoSXhHfDd4MQggtA0r7sPd/8rvtkezE6rfqZ+uj7zH0DffB+cT7b/mM+qb56/pI+ij/9wLKCBATth4KKbkx+zhLQT9CvESGRLM+wzdlLxQncR0tFEoNmwTw/Yz62vgv+zL9HwN5CD0NRhPTFlwY1hj4FNcQJAY0/lz1L+pZ4hfbP9LZzEzJqMc4xWPGcMb2xePKndHo1r3d+uFm4t7yT/7sBMMV0B0VHwop3y/RL1spWCcgHe8OuA5pBwv+KvgF8invxutn6znwL+pc7azs5+/j9cj1Evru/Fz1Qvbi9NvwAvCT7ZHsFOo58OL0+fq/ATUIGwmrDnAUmxXdFAYVsBG6D6QKegk+BeT+mPmG9ovxNe407Wrt4eu77XDx0fLK9qP3VPkR+bz2U/i/+BH5UP8eAlIJvxJkHT8o1THhOVdAaEIaRDBBpD3ZNCgrKSM1GQsQRgpjA8n+jvuA+yT9XgDuBUYK/A5wFIAVChiEGGMUeBBQCKL/k/Zc7ePkNt0A1dzO78lnyZrH+MZLyILJksqP0dvWF9u93ZjfmOjy9pr6IAxNF4QYHSQsLekteiuqJ7shlBFPEMELkv7T/Gn1jfLp8Hnu+vIo7rvtcPHk7br11/Z69zL9G/fG9JP2ou6/747qfehu5yLqRvCt9Wr+ZgVCCGcOtBQVFsMVmxXnEkAP6guwCa0HlQAX/Zj5d/U58FTwy+547Q3u3fEu8kL2svg5+QP5sviG9gD3QvYt+iT9bwLeDEsWhSGMLhM3cT8zQ3pFr0RlQII5WTAiJ94dSBTDDE4HvQBo/Y77Cf3//nEDDglKDW0SWRZNF8sa+xaWEi8N6wMt+lfyIOku4dDYudIPza3KMckIybfIGMp2yhDOTtPB1/zaydzL3eHrevdN/XkRDBncHE4p/zIkMQMt1ChbIKsOdg9cB4X+KPcT8kjxau297uDz8u0E8QLwBfKk+Cr4L/ue/Xj2q/RY8zXuhOxF5wLn4OKc6lTwbvhgAUQJtAtFEqsX1xkxFz8XhxFzDbAJ/wc+BXn/6/oq+Fjz9vBv8L/vRe8p7wfzFvSJ+LX6FPuz+RH5NPZ49ob2PPv8/FcECg+VGoEnyjNDPK1DAEVhRmlDVD4dNfIqaiGrF2kP9AkwBcr/dv1q/jX/igKUCNwLuxAuFUsWXBgnGd0U1Q8mB/D94PPh6z/jyNtE1RLPoct4y3jLeMuTy3jLX8wV0UTVxNnJ3ELc+OBv8Mv3OgN8ExgY0h4oKxcxnTBRKz8oLBzwD0APSgRA/Xf1wPBe7iXslO468aDtLvLn7wr1pvke+Wj9xPu59CX15u6F7cPpDOWg5MXiIOn28B75EAK8CJwNzxSrFzkcyhkwFvUSdQ4nCJIHHgLT/KP3d/WX8EXvAe9g76LuEfG28p/12vj5+gb7pvmw9yf2QvaX+DD8//5QCJYS0h5fK6g3m0DXRHBHSUgkQtg8QTLsJtkaiBJ8CrQDov/u/Kn7g/0AAD4F9AnfDSoSSBTDFWYWfhRREYgJHAED+ebusufA37XYntIezuXL5csozEXNJcobzOnO7NDl1MPYItnS2XznGPXa+PkM4hc2GnUo8DF2MdwtnylrIpQRGRDnCQn9YPhI8UXvUO7G6/jx1u2U7ufvfPA4+Bv3R/lq/v30/fT785HshOwO5lzk7OHK5Wrtj/Oe/SQGrwiHEfsWJxmhGU0X9RJND7AJoAfEBJT/s/mH9+Dz2/DA8ALwDu8c7wTxWPOT9rL4i/lH+fT3hvbX9gH4f/qS/oAEPg7OHOwmGjMQPrlCUESwRU1ChDowMJwn8hlFEowM3wRiApT/QP3Y/yoBCQblCKYL8A8mEA4SpxTyEGkP2Aj//jj4YO/n5hDf3thL0V3Lk8sny4LJ8ssny63Kpc4m077VFtom3DTcyuVf99z5zwurF5cbeSIULz8xhirOJFwhOwx5CGYFgPsW9Mvu5++r6+LsaPT28Hzw+PEc75X3J/bL90r7afVV8RXz1eyu7Tjno+YV4jXlW+x08477CQY1CO8OchX9FwoYqBWgEKYLMAXpAhACTPzo+Cf24vT48RPyB/Pp8EXvSPF+8e/0uvWy+JX3NPbj9Yf3X/dl+17/PAR1Dokb7CaFMpY9dUIaRF1E0UCpOGMuRCPFFmcOawgeAssA5P6u/noA0AOtB80Kcw1BEPAPsBFFEqwP0AwyBkD9d/Wf7P3jQtyx1VTOq8nSyIHIxcifyiXK48oSz6zS9tYK20LcrNv56cr2b/lYDT8XCRf1I34ubixLJ2EkzhwdCi4MkQYS+pP2HfBF7yXs8Ow88v7sW+yu7Wrtq/TU9OX2Iftm80vzaPQN7qLuIOkO5pzi2ebV7JvyjPpiAkoEYgvLEX4UIRVGE+EOOApNBsQEmQNo/fX4y/fF8zrx3vK08Yfuk+0d8ALwqvNc9Tb34/WE9Wn1UffN+N/7hwDfBGUNGxp8JDwvdTkcPcA+E0DoPTs3zi1VJdYY/xD5DFwHgQVUApYBOgNyBMoIOgtHC1gNSQypDUwOLgxGCrYE7vyf9aLuHugf4HPZ/NG8y8jKnsmOyGnKPciLxhnL98780RHXkNp/2Lnjn/X1+L4J5RlfGlQk4TCSMmAswyY1ImQM/QY6A9b1RvA+68Tq3ukK7JD0dPMx9F32P/QR+W/5Dffp+Znx5u4L7RLpOejv4/vitODF4lnrm/LC+tEEUgm6DwYVDBm8GXIV5BAeC6kEhwAY/tL7yPUl9Uz0gfOQ9K317/Q9843yqvPU9OL0QvaQ9FjzfvEi88b0APe2+8sAvAi0FHYgHi1kN30+00GFQ0pAeDszMtInlRrzEWILLgTaAYkBef+JAWYFygimC1gNug+RDz4OnQ6aDB0KdAVD/0f5SfJo7A7mOuD72aHUdNFy0IzPSM85zirNHs61z+DR5dSL1w/WE9jC4GjsmfGYAqsOARIJIIcrEC2yLI4nKCKTEB0KWQV7+MPykeyC6z7r4ux39Wn11PS/+DP1FPtj+iz56flY86Pv5u7r6dDpreTF4i3gcuHq6BruXfYqATwEcAt8E7cWJRjTFm0SBQzuBW8CXgCb+834yPXU9Kv04/Xy9mv2P/Ro9DH0NPau9tb1DPbS8/ryofaH9y/78f6MA3EMPxfWIWItwDU0Ozk+sz7LPKY2cS7aI00XkxCICfoEmwQQAukCngbnCbgOsBGlE5gTlBHLEQoPOwzKCAMCPPsJ9E/tOehl4YTbN9Uh0PTMbMz0zA/NvMt4y2DNStCg08/XVtgR14LacOjO8Jf4qAwcEoQYkCghLy0u8irdJbsYiAlCCBf9ufQQ8AjrdOtc7Znx5fb+9Xj2g/RC9s34QvYo9570ye0Z7SXsLOgD6Hfk+OC04ADmF+w98+780APKCK4QCRfXGeMYnBYKD+UIEgPz/1v9UfcJ9PryH/EF8p70ufSN8lfy3vIH88b0GfbG9D/0B/Pe8k71Rfj6+4b/qgW4DkQamSXwMWk6pD0kQmZBzD3eN/UsCyE6FLQLBwVDAHn/Pvx3/lYDBwWmC5EPXRCUEckQ1xDvDtAMlwplBKD+LPmo8vLt2+e04KvavdQ/0prPBM8rzq7L48pfzPfOMNEA1QPXo9WO2QzlQe0Y9YAELAsOEu0e3ibgJyInHCN4GX8MLAvcAmX7nvSN8n7xtPHZ98b8VvoI/Iv5Lfrp+Q/4ePbD8p3rteli6ADmyuW44vjgHt/i4zvpv++H96z9YAFfCfwO6RNwFMwSxg5GCt8EWQV9AuL9CPyO+4v59/ms/ar8zfgB+KH24POD9IHzjfIB7/Pur+4Q8JD0YPjf+ysCsgrsFdMfeisMM383JzsoPKs5pTViLekkGxptEsYOHQqhCMcGrQewCegK0w7yEHgQCg8UDQMLvAjFBX0Cuv2w91jzoO3r6RrlRt8j2jfVP9LQz9zOls2Gy07Kycs7z5HShtSL19DYINg/4/PuufSYArcNVRQxH08qjC6SKW8kphzQDD8Ghf539aDtmOj8653rIfKa+t36+vvE+5v7TPym+Q33IvOE7B7o2+cp5mvlPuJl4ZjfnOKn6efvk/a6/cACrwhPEPgUMBbpE+EObgqZA7EBDP/C+l/3rfVd9pX3SPoJ/S366Pgq+K721/YM9rbys/C77W3vf/Kf9Tv6lP/6BO0N/hgOIygrkjI6Nvg2tTdwNqownylMH+AWrhCLC9gI4wckBk4HiAmCDhwS5xJvE7sQZQ0sCzMHjAO6/fT3qPKg7Y7qy+ZZ4svdINhc0yPRwc4BzTTLnsnsx+XL6c4J0izXmde12Ffhk+3d8Wv/pgs+Dp8YESXgJyIniyXHIGoQBQx3B3b9Gfaz8Jbv8u2K8Nn39/k5+aT4U/jC+rz2a/ar9CbtVehw6B3nvubl5WnkgeLz5fnp6fBE9yT9vQBcBxIMNRETFekT4w9xDMgH3AJIA+X/Zfu/+PX4ifhi+Qn9tvvL91P4/fRp9T/0gfME8Svw6fDI9fX4lQDgBXALmBMeHPUj4ynELxozZjALMkswKixmJ8cgXxq0FKAQMQ5/DNsK5wmyCusMtw0XD4QP0g2yCkQJMgalAv393Pkw81Duw+ld5d3gQ91V1wvTStArzuPK48pOymnKKs0L0xPYC9w64EHk/uwl9S/7XQguDLARUBllHqsfgB6/G+oUiAnjB/39IPqr9JfwtvLb8K310PqM+p79jvtK+3P7LPmu9pD0Re/J7bjr+uqE7GXqPeoS6dPrk+3b8Cf2Bfpl+8r/+wWSB4kKEgwACaAHtANxA1IBoP4y/Tz73fpl+039Nf+s/ar8W/21+mX70Pro+A33vvc5+SP8Gv8XBswJaQ91F5od/SDeJkAphCn4JfkmhyJzHuUZgRZSEpEP0w7TDmkP1xAcEhMVgBXvF+IXtxY6FIcRjg3KCFcEQ/9H+e7ze+896qPmxeLm3YHZ89Sq0VTO1coWyX/HWMgYyj7R59XQ2EjgXORQ7rP54v0FDAsQxRb9IIgjFCdvJLgf9hvtDQYNHgIj/GD4LfFM9HX0UPb//t/7Nf81//n6Z/xs9+zyy+6X5xvmXOSe423mlOX25z3qbe+Q9FT5hv9XBDAFmgzvDtcQzhMCE50OIg3nCccGWQUSA//+nv3u/Hb9XP5r/1v9gPu1+qT4y/et9bfzmfFa9OL0HvlQ/8QEtQwfFJcb8SFmJ/Ussy3rLhAtayqqJ6IiZx+kGwkXchUCE28TwBOYE9EV+hXgFpwWwxWlE2oQ0Ax3BwMCTf2+94/z2O4U6ojm/ePA36LdL9mI1TLSms/LzBvMQ8wezqrRpdbv2n7gr+Vg7y/79ABHC40VehqgIdQo/iksJbshfRwKD7wIBAN7+Ffyo++L8afx7/RM/ED91f2i/5H9F/2/+Lr1pfB066fps+gR6GXqSur66q7tfvHy9uv6NP74A00GHQr8DkMRbRJeEf4PqQ2jCScIWgaYAvP/Jv6S/hj+rv4qAQv+0vt0/Nz5RfgM9rn0kPR19Gz3Mv0BAWsIhA9ZFhEc/yFzJ2kpTypgLD8oFCfAJAshIx84GwwZPxfCFIEW+BRyFXQWchWPFsMVmBMCE/wOmAtpBxACg/2y+Krz2O6z6DXlVeB43BTZQ9Qw0ejNocsozIbLH8+50s3WbN2o4Tbmou7a+JT/TgfyED0WFB7CJWcoPCY3I2UedBZxDFAIyf4l9WPxBPGn8Tzyl/ip++v6x/26/Vv9p/p49pvyau2z6AbqBel96BTqIuqR7LHvrvan+qz9YgJmBQAJcw3XELARJhAXDyINsgrzCGsILgT1AcsAbABsAOYA6AGi/7j8c/s7+rL4UPYK9db1dfTZ93f+2gHIB3UOVRTxGEoebyS0JS4mJCgFJogjzCMmIfoeDxvlGUEY7BV1FwkXqhYkFzEXThg/F3QWfhS7EFYMJwgtAxj+Eflo9KPv+enL5tTjVN9d3JrY5NOP0ZrPpM2xzc7O0dAa1MHXDd2P4rPo7vMV/FkFrhAnGeIgMShPKl0qsiRAIGYW6gvTBX/6hPVJ8invkPRo9H/6Nf80/isC1v4J/Vb6P/TA8MbrRece6A7mOegU6tLq/+1w8UD1BvvH/WIC7gUpCd4M/g+7EA0RnQ6BDfQJhQfFBfcC2AC9/+T+8/+wAL8BlgH//oX+dPz3+fX4X/et9eP1y/eO+1D/jwXACvIQBhXmGmUeuiBtI5YjryLJIZ8gqx8tHaQbhhlaF3QWSRU9FrYVPBUVFqgVIRUuFVQTDRHDDNgI0AOi/wb7KPc88nnuL+pu5zPkm+Gi3THaetUz0xXRtc/R0LvTvdTt2fff7+Pb573uJ/Zz+6IAVQtBECEVBh5qIasfgh/rHT8XtQxrCA8BbPer9Lby+vKB8/713/vt+3b9Xv/t+8L6NPbq8VDuL+p/6S3pSel27P/tBPEk9Ob3Ffz9/YkBMAXuBQAJmAsSDDsMVgz3C6EIkQadBR8DXgDW/rv+nv24/FD/hf5A/Qv+kv5B/qz95P4AADT+RgLrA9MFOAoGDYUQ9RKqFsoZXxpxHQYe9xynHaYcvxuhGWkYVxX1EkUSTxBAD8YOjg23Dd4MWA1kDHwKoQgJBqUCegDT/Ov65vcl9dLzfvG/77vt3un05vjgKN2o2PPUrdML08fSUNRk2F7dBODL5uLs7PId+G4BkQbACioSzxR+FIwUYRNBEDUIFwZ6AJr62vgP+Kb53frG/NoBBAO2BNMFtgRGAvD9EvoK9WPxGu5o7Fnrt+pb7KDtKe9y8sb0ePZs95r6m/sy/V4AUgEPAS0DwALrAxME3AI8BLMCOQJmBUgDgAQyBjMH7wb/Bx0KXwm+CR4LRAkACUQJJwivCMgHUAijCV0IcAtYDWUN/xCiERAT+BRJFasXdBaqFhYXVxUiFpkUBhX4FEYTLRR8ExwSbRLXEEwO+QzYCD8GOgMm/uv67/Ta79PrKeaN4ePbO9hr1OzQj9H80UHTOtf82jfeV+G+5vbnA+hA7B/xIvPO+doB4wfvDhgYHhzCHd8ephx1F2kPzwv3Aqz9OfnL95P2ofaL+ev6Vvoj/In4pvmE9VjzivAN7jLshe0Z7SnvK/AF8rbyWvQ09qT49fiP/Gr+egCABLsHEQvNClYMZQ0CCnwKhgjEBH4D9ABuAYb/YAHCA+sDVwSSB9YHawgMCPMIkQbgBUsFnQVZBQsHQQcdCrQLxg6wES0UdBZBGE4YGxqwGl8akxmSGMUWmxU6FGETzBKiEbsQTxCTEHYPJQ9zDeoL5Qg/BlIB/PxE93DxWesM5fff49v21tjU8dO70zfV4dqH3eDiG+bD6dPruOsy7JHsk+177znwHvk+/LQDaQ+iEa8ZPB4tHXEd+xZmFpcK6wPk/pL1FvTL7gvtiO/h687wY/H788v3Dfcg+kr7tfrt+z78Wfy1+un52vgB+JX3bviy+BL6MPzi/UgDIwWGCKYLpgsFDMMMRwvlCOIGEwQNAL8B1v4o/6QBiQEtA5EGGgiICToLOwznCZcK2AgMCKEIMwcYBxoIawiLC+sMXRCYE/gUnhewGnAcEh1zHowdYBuIGgoY3hXCFAESxw+RDxYOcw11Di8NtQxVCxsJrAbrA/H+f/pp9Q7vw+mU5Yrf49vQ2NvWzNXo1krZyNv13mjjeOWw5mXqjupn64T1gfPX9hsARgK7BzQQfhR+FPYTNhrXEHYPrA8XBs4C0/w+/B757PL5+tT04PPN+P712vgF+un5f/r1+Cz5IPrp+RH5Rfi+9+X2yvY5+bX6pvlB/pT/AQGqBZIHbgpTCswJHgtdCDYJhQcHBekCpAGKAs4CHwMLB+wEgwaVCaQKAgqXCgMLoQitB9gIyAdCCJQIbQk4ClYMcw2uEOYREhRLFnQWrxmyGwIbVh18GwIbAhvxGBgYWRZjFFISeRGgEHYPdg8+DsMMiwvZCQsHtgTLALb72ffq8YfuL+pd5cTh9d6g3ITbed1G3zfe3+E/48jkz+hi6EzrkOvW7UvzM/VZ/DYAmwQgDEwOpxS3FvgULhULEIIOdwdWAxwBb/nL9672TvW89uX2IPoD+S36xvzS+3T8Mv35+vf5Bfpv+Yv5Hvlu+Nr4KPfc+SH7Svu7/ij/9QEGBOIGlQmwCYsLlwpECVIJ8QczB3QFjANXBCsC3QPTBbgFJwgaCJUJfQv2CmUNpgt9C7QLbQlwC/QJiQrBC6QKTA5nDkMRExXsFdYY5RmwGnAc6BvoG7AaGRk/F94VIRXqFNsTihOkEioSyxG7EP4PSg2VCccGRgL//vn6DPZj8XbsR+jx5MThb98b3brbkdsP3ivfB+Jd5W7nfegI60/tT+2B80L21vX8/FEA3QNGCtAM7w7tDSMOgQ02CbAJYwO9APH++fqu/vz8QP0NAHb9KACG/7v+a/8w/G/5AfjW9eP1TvUn9nj24/U4+Iv5Svu7/uL9ef/YAA8BLgQ+BZ0FuQZLBYMG7wbuBTIGqgXQA4wD+gS4BTAFrQdrCDMH2QnNCqQK6AqwCV8JXAfvBq0HJgcXBsgHAAl6CTsMrA/JEAITIRW3FrkXoRnyGaEZaRiQFzEXBxZkFRMVfBOYE1QTfBMeEysTsBHwDxYOcQy+CU4HcgSJAcn+c/u/+PL2j/P28Gzuq+tV6HznUOXH42jjCePH43fkNuZV6PbnFOoi6jHrNe458Dzya/a1+qL/3QMCCgUMIg1ZDqgM9AmtB+sDQwAJ/Zr6LfrO+Zv7F/3T/K7+rv6g/uT+4v24/HH6YvkD+b/4pvkF+kj60PrE+0z8Mv3V/aD+u/6i/7AApAHrA/oEZgXiBnUGSwWqBcUF9wJ9AvcCRgJWAzAF4gZBB5cKtAtHC94M+QxVC7AJbQmvCPsFrAb/B60HygjPC+sMFw8cEi0UBhW3Fj8X4heDF/0XChg/F7cWZhYiFo0VSRWNFUgUVBPmEaAQJQ8iDcAKuwcHBdwCQwC7/oL8jPoB+EL27/RX8mDvru0G6gLn4+Qy403jgeLg4tTjd+Tz5R7oYujr6XTrneth8C7yGPXB+dL7yv/3AuAFoAdoBlAI3QPLADYAmvqa+rD3a/ZT+JL1+foX/fz8lgGHAFIBigJDAKIAg/2O+wX6KvjZ96P3RPc29/T3b/nc+an7nv1c/jX/2ABSAW8CHwPpAvcCHgJSAQMCzAF7AXsBEAL3AnIEWgbjB68IUgluClMK9AnBC7IKOArNCqQK9goRC38M6wyYCyINcw1lDWkPkQ8mEJMQbBFUE28TYxT4FAQU2xP2E0YTNxLYEdcQCg8+DhYO+QzPC9sK2Aj9BksF6wNUAr3/g/2p+wP55veG9gr1+vL28MzvQ+4a7njtaOyr61nrMeuc6oDqcel96ADmyuWU5RrlfOcg6QrsfPCD9Dn55P5iAqoFTQaFB04HPwZKBPQAQ//t+5j5cfpv+cL60Pq2+3b9GP4o/ygAkv4m/qr8FPtl+335VPk5+Tj4OfkR+Ur7I/yC/Hb9Tf2F/tj/yv+xAW4BbwLQA0oE7wZCCPMIAgrMCdwLRwuLCyINpgsSDGQMZAzSDUoN7Q1xDHALzwvnCaMJrwhOB04H7waGCA8KzQplDeEO4w8cElQT9hMEFDkTRRJPEJEP/A5lDbUMwQuyCs0KAwseC1MKUgn/B5EG+gQfAwEBNP6b+7P5bvgo99f2a/aS9Qr1nvQ98yHyRvCu7WfrweiJ51/moOQ15RrlDuZT5yDpZ+sm7ZfwS/PK9vn6kf1vAvgDuAUaCAsHWQVXBIkB8f7E+yD6svhg+H35IPo+/KD+UP8qAcwB2gHmAGv//f22+y363PmJ+Cz5Evo7+hf9Jv41/+gBvwHCA5sEcgQkBsUF/QZpB+MHegk2CSoKAwtHC38MmAsSDCAM9wsuDAUMiwsFDBELtAuLC0cLEQssC2EK6ApuChELYgvBCyAMwwz5DPsNMQ5nDmcOgg4IDkwOZw4+Du0Ntw1lDesMEgxiC4kKKQkaCGgG+gTdA0YCKgFe/+L9nfxl+2P6v/ij97z2M/Ul9YHzjfLP8VTwYO+u7Sbtgusi6krqVeia6dDpnOrW7b/v0fJr9kf5j/x3/ssAewFGAowDAwJuAV4AXv8o//D9aP1N/Vv9g/1q/uT+Gv+v/6//bAAbAOX/AABe/1D/8f7J/gz/KP+U/1EAsAAqAYoC+AOABGYFuQb9BrsHygjzCA4JRAkCCswJ5wmyCkYKwApHCx4LtAt9C9wLSQwgDFYMcQy1DEoN6ww9DfkMLgzeDCAMRwuYC5cKsgr2ChELpgv3C/kMcw3SDRcPgg5MDsQNmgzcC80K5wmjCYYIUAigBzMH4gb7BcQEOgNSARsAd/5A/SP83fo7+n35R/k5+Sr4y/dr9kD1TPSo8jzy2/Bg7+bulO6U7rHvRvC08bbydfTl9r/4c/t2/V7/9ACJAbMCAwJgAdgAyf6e/br9qvyq/DL9XP6u/igAiQF9AtwCzgKzAgMCOQIQAqQBAwLaAaUCtAO2BAkG1AZpB/8HoAdQCOMHoAfxBwsHaQfWB10IGwmVCXwKbgqyClULYgumC6YLwQu0C4wMBg1lDQgO7Q3fDbcNPQ2aDLQLwAr0CXoJ8wiICVIJAgqXChELwQv3C5oMqAw7DIsLpArMCcoI8QfHBgkGFQWABCEE+ANxA1YDRgJ7AYcAvf+F/hf90vun+iz52vh7+B34Ufco97z24/VC9hn2M/X99Mb0GPXW9Xr3D/i/+N36L/t0/K7+rv5r/0P/ef+G/9b+Xv80/hf9rP1A/Xb9NP7k/qL/8//1AdoBbgHpAugBYAG/AeYA2gGxAegBfgPrA2YFkQYzB8oI5QjlCNkJ8whSCcoIUAhQCK0H8QeUCNgIiAmjCXwKEQs6C+oLBQzPC9wL6AoDC9sKHQpuCgIKOAoqCjgK6ArACs0KsgpuCm4K5wkpCfMIlAgnCP8H8QdQCEIIvAjlCLwIDgmGCFAIdwdaBj4FEwR+A4oCHgIDAr8BYAFgAUUBywBDACj//f2d/Er7IPqY+dr4Hfjm9x34YPiL+SD60PqA+0z8Wfzh/Mb8uPwI/I77c/tX+477nfxb/eT+AABuAX0CSAMEA2ICewHmANj/Xv+g/uT+1v6v/xwBzAGMA/gDcgS4BUsFgQUjBZsEEwTdA9ADBgSbBEsFuAWeBsgHDgm+CR0KiQrbCgMLpgumC6YL6gvPC9wLwQuLCxELfArMCbAJUgkOCfMIKQlECV8J2QmwCW0JRAmUCDUIaQeRBvsFdAUHBakE7ATRBNEE+gT6BN8EMAW4BcUFxQXFBWYFMAUwBcQE0ANIA30C6AEBAaIADQD//rv+Jv5b/Qn9I/yA+3P76/pI+qf6f/qa+sT7qvx2/TT+Gv9Q/8r/hwAoAOX/hv9e/6D+1v4a/zX/ov+HAA8BOQJIAwQDfgPQA84CigJGAqQBRQF7AR4C9wJyBI8FgwZ3B7sHTgcmB+AFxASMA2ICbwJUAvcCgATFBUEHvAgCClULcAuLC8AKbQnYCP8HTgfUBpEGgwa5BqAH4wfjBwwIuwdOB/0GrAaRBu4FgQUjBfoE0QRKBBMEmQP3ApgCOQJvAjkCRgJiAukCHwP4A0oEmQOMA84C9QFuAUMAQ//W/qD+av6u/kP/hv8AAEMAegDmADYA5f+i//H+8f7x/sn+5f+iAGwAKgF7ARwBYAH0AJUAKAAoAEMA2ADaAcACOgMhBHIEmwTrA3EDfQKkASoBDwFuAUYC9wLfBAkGgwatB1wHngbuBesDVAK9APP/a/9r/zYARQEEA/oEgwb/B9gIvAgOCbwIrQeeBnQFgATQAxMEZQSNBD4FgQXFBT8GngZ1Bj8GjwXsBLYEVwTdA2MDfQIDApYBbgGWATcBUgGkATkCOgMTBOwEWQWBBT4F3wRXBFYDYgIcAdj/Q//k/ij/5f8oAAEBsQGKAi0DSAM6A1QCewGwANj/Gv9P/kH+uv0Y/sn+KP8NANgAKgGJAQMCVALMAfUBewEPAeYAywA3ASoBRQHaAfUBswI6AzoDjAOnA9ADmQNjAxIDVAL1Ab8BNwEqAQ8BywAPAW4BiQG/ASsCfQJiAjoDjAN+AwYEZQQ8BHIEPARKBNADYwM6AwQDOgNWA0gD3QMuBPoESwVZBeAFjwUHBfoEwgM6A+kCbwJUAvUBHgJvAgQDBgQhBAYE+ANWA/cCmALaAfQANgDz//P/UQAPAVIBzAFvAtwCfgO0A90D3QOnA4wDSAMtA9wCYgIQAnsBsAC9AOX/5f95/2v/a/+U/ygAhwD0AGABpAG/AbEBsQFgAZUANgDl/yj/Nf9e//H+Q/+G/w0AQwC9ACoBDwEBARwBywAcAUUBYAG/AXsBUgFgATcBRQFRAKL/ef///lD/hv/K/9j/AABeALAAAQG9ADYA8/8NAAAAhwDYAPQADwEcAQMCHgL1AQMCewEPARwBAQEPASoBDwEPASoBpAEQAooCfQKYAjkCmALAAs4CigJUAgMC2gErAooCswLcArMCpQKzAm8COQJuAbAA8/+v/2v/ov/z/1EAhwDmAHsBwAItAy0DpQI5AgMC6AG/AW4BhwBeAA0AQwCVAHoAQwANAAAAGwBDAIcAywAPAW4BbgGkAb8BbgHmAJUA5f/K/73/lP+G/17/ef+U/3n/lP9e/zX/1v40/k/+XP6g/nf+u/7k/l7/8/+HAAEBYAE3AVIB9AABAVEAr//J/uL9W/0X/Qn9F/0J/YP9C/4M/5T/egDmAPQADwFgATcBsABsAMr/UP/W/mr+Qf4Y/vD9nv39/ZL+8f7z/1EA2AD0ABwB2ABsAL3/5P6g/ib+GP6F/lD/GwCiAKQB2gE5AhAClgHYAL3/1v4m/qz91f12/br9GP5q/ij/yv8NAIcAsAC9AOYADwEqAeYA5gCHADYA2P9D///+rv5P/uL98P3w/UH+yf5Q/9j/egDYAG4B6AFGAr8BYAEPARsAyv9Q/8n+d/4Y/mr+XP7//nn/r/8bACgAGwBDAJT/KP+u/sf9rP2R/eL9/f2F/hr/hv8oAFEAXgBDANj/Nf+g/ib+C/7i/dX9Jv4L/k/+oP7J/hr/8f6g/vH+rv6g/uT+KP8o/xr/Q/8o//H+yf7w/YP9F/2q/Mb87vx2/cf9kv5D//P/lQCHAGwAAACg/qz9JP2C/Ez8gvzG/Fv9hf69/3oA5gDYAIcAGwCi/4X+g/3h/Gf8FfxZ/Pz8rP13/gz/Q//Y/+X/DQDY/0P/8f7k/uT+UP9r/17/Gv///v/+u/5c/gv+kf1b/UD91f13/hr/ef+9/5T/vf+v/5T/u/40/uL9dv3H/f39kv4o/8r/XgDLAPQAywA=\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 16
}
]
},
{
"cell_type": "code",
"source": [
"rate,speech = read(Main_Wav_Data['WAV'][100])\n",
"print(Main_Wav_Data['EMOTION'][100])\n",
"print(speech.shape)\n",
"print(speech.dtype)\n",
"print(rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "4ztO-WAxtyax",
"outputId": "ce410cf2-d0f5-4b84-cea3-3e1bec1300c0"
},
"execution_count": 17,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"OAF_neutral\n",
"(48876,)\n",
"int16\n",
"24414\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Waveplot"
],
"metadata": {
"id": "-CNUh7qat_z_"
}
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"audio_speech,rate = librosa.load(Main_Wav_Data['WAV'][120])\n",
"librosa.display.waveplot(audio_speech, sr=rate, color = '#ff0066')\n",
"Audio(audio_speech, rate=rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "DyIb7d54t_Ou",
"outputId": "63bbfaa1-0812-4a8c-9326-c76f41ff4a2e"
},
"execution_count": 18,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 18
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"audio_speech,rate = librosa.load(Main_Wav_Data['WAV'][10])\n",
"librosa.display.waveplot(audio_speech, sr=rate, color = '#00cc99')\n",
"Audio(audio_speech, rate=rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "9nJSggf5tXTn",
"outputId": "60dd4b93-2796-46a0-9fcf-24a4251d81b4"
},
"execution_count": 19,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 19
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Noise:"
],
"metadata": {
"id": "N6oEqdaKyfEz"
}
},
{
"cell_type": "code",
"source": [
"def add_noise(data):\n",
" noise_value = 0.015 * np.random.uniform() * np.amax(data)\n",
" data = data + noise_value * np.random.normal(size=data.shape[0])\n",
" return data"
],
"metadata": {
"id": "X4ZZCy8Kypqa"
},
"execution_count": 20,
"outputs": []
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"\n",
"audio_speech,sample_rate = librosa.load(Main_Wav_Data['WAV'][2000])\n",
"\n",
"noise_injection = add_noise(audio_speech)\n",
"\n",
"librosa.display.waveplot(noise_injection, sr=sample_rate)\n",
"Audio(noise_injection, rate=sample_rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "Gp7xBCfFyZXS",
"outputId": "f0dc9b98-48c9-4a2f-e492-39e5b6f2f889"
},
"execution_count": 21,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 21
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Stretch:"
],
"metadata": {
"id": "ARSRbwbZyyII"
}
},
{
"cell_type": "code",
"source": [
"def stretch_process(data, rate=0.8):\n",
" return librosa.effects.time_stretch(data, rate)"
],
"metadata": {
"id": "ponvw8bByuHE"
},
"execution_count": 22,
"outputs": []
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"\n",
"audio_speech,sample_rate = librosa.load(Main_Wav_Data['WAV'][2000])\n",
"\n",
"stretching_audio = stretch_process(audio_speech)\n",
"librosa.display.waveplot(stretching_audio, sr=sample_rate, color='#cc0000')\n",
"Audio(stretching_audio, rate=sample_rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "SA-nisAkyuEo",
"outputId": "98455b7f-8829-4896-851a-1455424c2ef1"
},
"execution_count": 23,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 23
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Shifting:"
],
"metadata": {
"id": "OTVn1ToSzBXf"
}
},
{
"cell_type": "code",
"source": [
"def shift_process(data):\n",
" shift_range = int(np.random.uniform(low=-5, high=5) * 1000)\n",
" return np.roll(data, shift_range)"
],
"metadata": {
"id": "VERJK71zzIu_"
},
"execution_count": 24,
"outputs": []
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"\n",
"audio_speech,sample_rate = librosa.load(Main_Wav_Data['WAV'][2000])\n",
"\n",
"shifting_audio = shift_process(audio_speech)\n",
"librosa.display.waveplot(shifting_audio, sr=sample_rate, color='purple')\n",
"Audio(shifting_audio, rate=sample_rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "0aRkdd2Sy9s_",
"outputId": "bed5aa53-da7e-43de-889e-13ebd0e5e55d"
},
"execution_count": 25,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 25
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Pitch:"
],
"metadata": {
"id": "VwNjl1slzX8n"
}
},
{
"cell_type": "code",
"source": [
"def pitch_process(data,sampling_rate,pitch_factor=0.7):\n",
" return librosa.effects.pitch_shift(data,sampling_rate, pitch_factor)"
],
"metadata": {
"id": "9g_zjVAdzcAP"
},
"execution_count": 26,
"outputs": []
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"\n",
"audio_speech,sample_rate = librosa.load(Main_Wav_Data['WAV'][2000])\n",
"\n",
"pitch_audio = pitch_process(audio_speech, sample_rate)\n",
"librosa.display.waveplot(pitch_audio, sr=sample_rate, color='orange')\n",
"Audio(pitch_audio, rate=sample_rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "eR2s8KCPy9qq",
"outputId": "94c68397-cf64-425a-cdff-66c123bb69fe"
},
"execution_count": 27,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 27
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"* Sound: sequence of vibrations in varying pressure strengths (y)\n",
"* The sample rate (sr) is the number of samples of audio carried per second, measured in Hz or kHz"
],
"metadata": {
"id": "NJS7Yx-864zL"
}
},
{
"cell_type": "code",
"source": [
"# Importing 1 file\n",
"y, sr = librosa.load(Main_Wav_Data['WAV'][2000])\n",
"\n",
"print('y:', y, '\\n')\n",
"print('y shape:', np.shape(y), '\\n')\n",
"print('Sample Rate (KHz):', sr, '\\n')\n",
"\n",
"# Verify length of the audio\n",
"print('Check Len of Audio:', np.shape(y)[0]/sr)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "WUiryy6v65hy",
"outputId": "08abbd1b-8c57-4d8f-c075-c143deca10e5"
},
"execution_count": 28,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"y: [ 0.00030614 0.00074618 0.00033639 ... -0.00029043 0.00022785\n",
" 0. ] \n",
"\n",
"y shape: (38635,) \n",
"\n",
"Sample Rate (KHz): 22050 \n",
"\n",
"Check Len of Audio: 1.752154195011338\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# Trim leading and trailing silence from an audio signal (silence before and after the actual audio)\n",
"audio_file, _ = librosa.effects.trim(y)\n",
"\n",
"# the result is an numpy ndarray\n",
"print('Audio File:', audio_file, '\\n')\n",
"print('Audio File shape:', np.shape(audio_file))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "kI_0Z79r7TpZ",
"outputId": "6d210331-795a-4b03-ea9f-a0993c33a393"
},
"execution_count": 29,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Audio File: [ 0.00030614 0.00074618 0.00033639 ... -0.00029043 0.00022785\n",
" 0. ] \n",
"\n",
"Audio File shape: (38635,)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize = (13, 6))\n",
"librosa.display.waveplot(y = audio_file, sr = sr, color = 'green');\n",
"plt.title('Sound Waves');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "SliORbB97W4A",
"outputId": "b7f30e73-019d-47e9-b3b5-68a35d3d5f26"
},
"execution_count": 30,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Fourier Transform:\n",
"\n",
"Function that gets a signal in the time domain as input, and outputs its decomposition into frequencies\n",
"Transform both the y-axis (frequency) to log scale, and the “color” axis (amplitude) to Decibels, which is approx. the log scale of amplitudes."
],
"metadata": {
"id": "e-YD3Nw2Ed66"
}
},
{
"cell_type": "code",
"source": [
"# Default FFT window size\n",
"n_fft = 2048 # FFT window size\n",
"hop_length = 512 # number audio of frames between STFT columns (looks like a good default)\n",
"\n",
"# Short-time Fourier transform (STFT)\n",
"D = np.abs(librosa.stft(audio_file, n_fft = n_fft, hop_length = hop_length))\n",
"\n",
"print('Shape of D object:', np.shape(D))\n",
"\n",
"plt.figure(figsize = (13, 6));\n",
"plt.plot(D);"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "uttV7BkY51YL",
"outputId": "ffd448a0-3c66-4d0c-fa3b-7addee05c181"
},
"execution_count": 31,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Shape of D object: (1025, 76)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"The Spectrogram:\n",
"\n",
"* What is a spectrogram? A spectrogram is a visual representation of the spectrum of frequencies of a signal as it varies with time. When applied to an audio signal, spectrograms are sometimes called sonographs, voiceprints, or voicegrams (wiki).\n",
"* Here we convert the frequency axis to a logarithmic one."
],
"metadata": {
"id": "5d9nW-8yucz9"
}
},
{
"cell_type": "code",
"source": [
"figure = plt.figure(figsize=(13,6))\n",
"\n",
"audio_speech,rate = librosa.load(Main_Wav_Data['WAV'][2000])\n",
"\n",
"stft_audio = librosa.stft(audio_speech)\n",
"Db_audio = librosa.amplitude_to_db(abs(stft_audio))\n",
"librosa.display.specshow(Db_audio, sr=rate, x_axis='time', y_axis='hz')\n",
"Audio(audio_speech, rate=rate)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "tuuMsLgZtXRY",
"outputId": "cb5ce622-2c55-4a03-a3b9-594d640b1bfe"
},
"execution_count": 32,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.lib.display.Audio object>"
],
"text/html": [
"\n",
" <audio controls=\"controls\" >\n",
" <source 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\" type=\"audio/wav\" />\n",
" Your browser does not support the audio element.\n",
" </audio>\n",
" "
]
},
"metadata": {},
"execution_count": 32
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Mel Spectrogram:\n",
"\n",
"The Mel Scale, mathematically speaking, is the result of some non-linear transformation of the frequency scale. The Mel Spectrogram is a normal Spectrogram, but with a Mel Scale on the y axis."
],
"metadata": {
"id": "Wd-IFKjU76pF"
}
},
{
"cell_type": "code",
"source": [
"S = librosa.feature.melspectrogram(y, sr=sr)\n",
"S_DB = librosa.amplitude_to_db(S, ref=np.max)\n",
"\n",
"plt.figure(figsize = (13, 6))\n",
"librosa.display.specshow(S_DB, sr=sr, hop_length=hop_length, x_axis = 'time', y_axis = 'log', cmap = 'cool')\n",
"plt.colorbar()\n",
"plt.title('Mel Spectrogram');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "WTYtvTjM77QO",
"outputId": "bbadd6df-18cb-4c4b-ec47-e5d9586e70e6"
},
"execution_count": 33,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Zero Crossing Rate:\n",
"\n",
"the rate at which the signal changes from positive to negative or back."
],
"metadata": {
"id": "6YXJIimH8XpQ"
}
},
{
"cell_type": "code",
"source": [
"# Total zero_crossings in our 1 song\n",
"zero_crossings = librosa.zero_crossings(audio_file, pad=False)\n",
"print(sum(zero_crossings))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "FDx3j3Xy51V6",
"outputId": "81c59f8e-8db6-46ab-ca0a-d34a431bf354"
},
"execution_count": 34,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"6512\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Harmonics and Perceptrual:\n",
"\n",
"* Harmonics are characteristichs that human years can't distinguish (represents the sound color)\n",
"* Perceptrual understanding shock wave represents the sound rhythm and emotion"
],
"metadata": {
"id": "zSSQQ4pw8dBV"
}
},
{
"cell_type": "code",
"source": [
"y_harm, y_perc = librosa.effects.hpss(audio_file)\n",
"\n",
"plt.figure(figsize = (13, 6))\n",
"plt.plot(y_harm, color = '#cc0000');\n",
"plt.plot(y_perc, color = '#00cc99');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "gxfiivrv51Tv",
"outputId": "b2538e36-3547-4c34-effc-3aed0b97b8a9"
},
"execution_count": 35,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Tempo BMP (beats per minute):\n",
"\n",
"Dynamic programming beat tracker."
],
"metadata": {
"id": "3kp-z6Im8q9y"
}
},
{
"cell_type": "code",
"source": [
"tempo, _ = librosa.beat.beat_track(y, sr = sr)\n",
"tempo"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "nDgO25lT51Rj",
"outputId": "1e205dcd-b276-4688-c682-1e471778e670"
},
"execution_count": 36,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"129.19921875"
]
},
"metadata": {},
"execution_count": 36
}
]
},
{
"cell_type": "markdown",
"source": [
"Spectral Centroid:\n",
"\n",
"indicates where the ”centre of mass” for a sound is located and is calculated as the weighted mean of the frequencies present in the sound."
],
"metadata": {
"id": "gmHW3sxu8y1k"
}
},
{
"cell_type": "code",
"source": [
"# Calculate the Spectral Centroids\n",
"spectral_centroids = librosa.feature.spectral_centroid(audio_file, sr=sr)[0]\n",
"\n",
"# Shape is a vector\n",
"print('Centroids:', spectral_centroids, '\\n')\n",
"print('Shape of Spectral Centroids:', spectral_centroids.shape, '\\n')\n",
"\n",
"# Computing the time variable for visualization\n",
"frames = range(len(spectral_centroids))\n",
"\n",
"# Converts frame counts to time (seconds)\n",
"t = librosa.frames_to_time(frames)\n",
"\n",
"print('frames:', frames, '\\n')\n",
"print('t:', t)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "IoOZ3Kf48v97",
"outputId": "e03758c8-64d7-4f3e-bd38-68cb7bb39214"
},
"execution_count": 37,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Centroids: [4940.81963865 6327.19463118 7147.81406484 7752.32331513 8004.54346528\n",
" 7990.01579971 8005.93588733 7957.94827651 7797.22797633 6310.81643739\n",
" 3279.09322006 2664.78532369 2631.25781323 2566.73179974 2627.15740144\n",
" 2819.78331455 3224.48576058 3843.56539196 4806.35431336 5406.27442188\n",
" 5444.47310102 5072.59530844 2943.16009658 2443.31665555 2150.72912428\n",
" 1725.34703627 1164.05799605 1155.83636326 1318.05302636 1481.35494691\n",
" 1701.47277336 1839.58222888 2176.9348766 2441.37694799 2541.38609607\n",
" 2422.7741886 2234.10895978 2029.68147735 1726.38485802 1407.71301498\n",
" 1181.01450703 1784.48264945 1892.81627973 1691.74903522 1869.05530676\n",
" 1571.74054844 1184.3062587 915.33896235 807.16829463 975.44375381\n",
" 1260.3584256 1521.98146897 1726.92834366 1949.94052756 2280.65694901\n",
" 2827.52662501 2980.44264109 2431.299773 2215.81878622 2378.77648939\n",
" 2274.24057491 2320.91718291 2365.44433307 2452.29295107 2500.69006128\n",
" 2382.51499047 1565.09698128 1208.08903789 1308.34128018 1303.73210785\n",
" 1381.89794264 1741.86718318 1985.07325458 2000.30186055 2005.20809558\n",
" 2433.90090006] \n",
"\n",
"Shape of Spectral Centroids: (76,) \n",
"\n",
"frames: range(0, 76) \n",
"\n",
"t: [0. 0.02321995 0.04643991 0.06965986 0.09287982 0.11609977\n",
" 0.13931973 0.16253968 0.18575964 0.20897959 0.23219955 0.2554195\n",
" 0.27863946 0.30185941 0.32507937 0.34829932 0.37151927 0.39473923\n",
" 0.41795918 0.44117914 0.46439909 0.48761905 0.510839 0.53405896\n",
" 0.55727891 0.58049887 0.60371882 0.62693878 0.65015873 0.67337868\n",
" 0.69659864 0.71981859 0.74303855 0.7662585 0.78947846 0.81269841\n",
" 0.83591837 0.85913832 0.88235828 0.90557823 0.92879819 0.95201814\n",
" 0.9752381 0.99845805 1.021678 1.04489796 1.06811791 1.09133787\n",
" 1.11455782 1.13777778 1.16099773 1.18421769 1.20743764 1.2306576\n",
" 1.25387755 1.27709751 1.30031746 1.32353741 1.34675737 1.36997732\n",
" 1.39319728 1.41641723 1.43963719 1.46285714 1.4860771 1.50929705\n",
" 1.53251701 1.55573696 1.57895692 1.60217687 1.62539683 1.64861678\n",
" 1.67183673 1.69505669 1.71827664 1.7414966 ]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# Plotting the Spectral Centroid along the waveform\n",
"\n",
"# Function that normalizes the Sound Data\n",
"def normalize(x, axis=0):\n",
" return sklearn.preprocessing.minmax_scale(x, axis=axis)\n",
" \n",
"plt.figure(figsize = (13, 6))\n",
"librosa.display.waveplot(audio_file, sr=sr, color = '#ff9966');\n",
"plt.plot(t, normalize(spectral_centroids), color='#66ccff');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "fuHfyGyD8v7s",
"outputId": "dc818d45-ff46-49f9-ca90-73c2b7207ae2"
},
"execution_count": 38,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Spectral Rolloff:\n",
"\n",
"is a measure of the shape of the signal. It represents the frequency below which a specified percentage of the total spectral energy, e.g. 85%, lies"
],
"metadata": {
"id": "fxb5gs8F9Z7p"
}
},
{
"cell_type": "code",
"source": [
"# Spectral RollOff Vector\n",
"spectral_rolloff = librosa.feature.spectral_rolloff(audio_file, sr=sr)[0]\n",
"\n",
"# The plot\n",
"plt.figure(figsize = (13, 6))\n",
"librosa.display.waveplot(audio_file, sr=sr, alpha=0.4, color = '#A300F9');\n",
"plt.plot(t, normalize(spectral_rolloff), color='#FFB100');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "bFqVRt9P9bgV",
"outputId": "cb172a77-27f4-47be-fa9f-f27887af53a0"
},
"execution_count": 39,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"Mel-Frequency Cepstral Coefficients:\n",
"\n",
"The Mel frequency cepstral coefficients (MFCCs) of a signal are a small set of features (usually about 10–20) which concisely describe the overall shape of a spectral envelope. It models the characteristics of the human voice."
],
"metadata": {
"id": "pvUqmCryFsTx"
}
},
{
"cell_type": "code",
"source": [
"mfccs = librosa.feature.mfcc(audio_file, sr=sr)\n",
"print('mfccs shape:', mfccs.shape)\n",
"\n",
"# Displaying the MFCCs\n",
"plt.figure(figsize = (13, 6))\n",
"librosa.display.specshow(mfccs, sr=sr, x_axis='time', cmap = 'cool');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 0
},
"id": "d1SISeg2FuV2",
"outputId": "cf9d6765-4fbd-4bb0-8592-2291bb595a49"
},
"execution_count": 40,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"mfccs shape: (20, 76)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 1 Axes>"
],
"image/png": "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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"# <a name='Preprocessing'></a>\n",
"\n",
"<div style=\"border-radius:10px;\n",
" background-color:#ffffff;\n",
" border-style: solid;\n",
" border-color: #0b0265;\n",
" letter-spacing:0.5px;\">\n",
"\n",
"<center><h3 style=\"padding: 5px 0px; color:#0b0265; font-weight: bold; font-family: Cursive\">\n",
"3. Preprocessing</h3></center>\n",
"</div>\n",
"\n",
"<a href=\"#toc\" class=\"btn btn-primary btn-sm\" role=\"button\" aria-pressed=\"true\" style=\"color:white\" data-toggle=\"popover\">Back to Table of Contents</a>"
],
"metadata": {
"id": "FLk0Nenl2p_1"
}
},
{
"cell_type": "code",
"source": [
"def extract_process(data):\n",
" \n",
" output_result = np.array([])\n",
" mean_zero = np.mean(librosa.feature.zero_crossing_rate(y=data).T,axis=0)\n",
" output_result = np.hstack((output_result,mean_zero))\n",
" \n",
" stft_out = np.abs(librosa.stft(data))\n",
" chroma_stft = np.mean(librosa.feature.chroma_stft(S=stft_out,sr=sample_rate).T,axis=0)\n",
" output_result = np.hstack((output_result,chroma_stft))\n",
" \n",
" mfcc_out = np.mean(librosa.feature.mfcc(y=data,sr=sample_rate).T,axis=0)\n",
" output_result = np.hstack((output_result,mfcc_out))\n",
" \n",
" root_mean_out = np.mean(librosa.feature.rms(y=data).T,axis=0)\n",
" output_result = np.hstack((output_result,root_mean_out))\n",
" \n",
" mel_spectogram = np.mean(librosa.feature.melspectrogram(y=data,sr=sample_rate).T,axis=0)\n",
" output_result = np.hstack((output_result,mel_spectogram))\n",
" \n",
" return output_result"
],
"metadata": {
"id": "iorc5Fl4yE7B"
},
"execution_count": 39,
"outputs": []
},
{
"cell_type": "code",
"source": [
"def export_process(path):\n",
" \n",
" data,sample_rate = librosa.load(path,duration=2.5,offset=0.6)\n",
" \n",
" output_1 = extract_process(data)\n",
" result = np.array(output_1)\n",
" \n",
" noise_out = add_noise(data)\n",
" output_2 = extract_process(noise_out)\n",
" result = np.vstack((result,output_2))\n",
" \n",
" new_out = stretch_process(data)\n",
" strectch_pitch = pitch_process(new_out,sample_rate)\n",
" output_3 = extract_process(strectch_pitch)\n",
" result = np.vstack((result,output_3))\n",
" \n",
" return result"
],
"metadata": {
"id": "Fqm8mfndx7vi"
},
"execution_count": 40,
"outputs": []
},
{
"cell_type": "code",
"source": [
"X_train, y_train = [],[]\n",
"\n",
"for path,emotion in zip(Main_Wav_Data.WAV, Main_Wav_Data.EMOTION):\n",
" \n",
" features = export_process(path)\n",
" \n",
" for element in features:\n",
" X_train.append(element)\n",
" y_train.append(emotion)"
],
"metadata": {
"id": "ImZ2YIG-tWEA"
},
"execution_count": 42,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print(len(X_train))\n",
"print(len(y_train))\n",
"print(len(Main_Wav_Data.WAV))\n",
"print(X_train[0].shape)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "y4uGEtrC0wbr",
"outputId": "b2755137-005d-4f48-8d08-c727e42e6cb3"
},
"execution_count": 45,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"8400\n",
"8400\n",
"2800\n",
"(162,)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"New_Features_Wav = pd.DataFrame(X_train)\n",
"New_Features_Wav['EMOTIONS'] = y_train\n",
"\n",
"New_Features_Wav.to_csv('New_Wav_Set.csv', index=False)\n",
"New_Features_Wav.head(5)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 386
},
"id": "gAFDda640oJ3",
"outputId": "c8cd1dd3-2138-4f45-97b4-694074ec0680"
},
"execution_count": 47,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" 0 1 2 3 4 5 6 \\\n",
"0 0.055575 0.292345 0.479627 0.334613 0.322109 0.370994 0.479266 \n",
"1 0.056934 0.296830 0.485121 0.340952 0.328351 0.380511 0.482851 \n",
"2 0.058665 0.289988 0.264271 0.457303 0.307444 0.269937 0.336408 \n",
"3 0.103018 0.377496 0.464786 0.470453 0.400674 0.388081 0.408613 \n",
"4 0.106507 0.401849 0.487043 0.484786 0.417820 0.424877 0.448959 \n",
"\n",
" 7 8 9 ... 153 154 155 156 \\\n",
"0 0.933623 0.586313 0.332760 ... 0.000010 0.000021 0.000015 0.000016 \n",
"1 0.934719 0.588867 0.338838 ... 0.000011 0.000021 0.000015 0.000016 \n",
"2 0.464787 0.964446 0.542665 ... 0.000003 0.000002 0.000003 0.000005 \n",
"3 0.528203 0.540592 0.444656 ... 0.000293 0.000488 0.000507 0.000489 \n",
"4 0.548388 0.561508 0.470152 ... 0.000318 0.000503 0.000530 0.000506 \n",
"\n",
" 157 158 159 160 161 \\\n",
"0 0.000012 0.000005 8.710197e-07 8.116926e-08 1.533833e-08 \n",
"1 0.000013 0.000005 1.573915e-06 8.838117e-07 8.187312e-07 \n",
"2 0.000003 0.000003 4.845274e-07 1.509497e-08 5.118255e-10 \n",
"3 0.000298 0.000162 4.025916e-05 2.583791e-06 2.853317e-08 \n",
"4 0.000315 0.000180 6.180123e-05 2.451167e-05 2.173154e-05 \n",
"\n",
" EMOTIONS \n",
"0 OAF_neutral \n",
"1 OAF_neutral \n",
"2 OAF_neutral \n",
"3 OAF_Pleasant_surprise \n",
"4 OAF_Pleasant_surprise \n",
"\n",
"[5 rows x 163 columns]"
],
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" <th></th>\n",
" <th>0</th>\n",
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" <th>EMOTIONS</th>\n",
" </tr>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0.055575</td>\n",
" <td>0.292345</td>\n",
" <td>0.479627</td>\n",
" <td>0.334613</td>\n",
" <td>0.322109</td>\n",
" <td>0.370994</td>\n",
" <td>0.479266</td>\n",
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" <td>8.710197e-07</td>\n",
" <td>8.116926e-08</td>\n",
" <td>1.533833e-08</td>\n",
" <td>OAF_neutral</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.056934</td>\n",
" <td>0.296830</td>\n",
" <td>0.485121</td>\n",
" <td>0.340952</td>\n",
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" <td>1.573915e-06</td>\n",
" <td>8.838117e-07</td>\n",
" <td>8.187312e-07</td>\n",
" <td>OAF_neutral</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>0.058665</td>\n",
" <td>0.289988</td>\n",
" <td>0.264271</td>\n",
" <td>0.457303</td>\n",
" <td>0.307444</td>\n",
" <td>0.269937</td>\n",
" <td>0.336408</td>\n",
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" <td>0.000003</td>\n",
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" <td>4.845274e-07</td>\n",
" <td>1.509497e-08</td>\n",
" <td>5.118255e-10</td>\n",
" <td>OAF_neutral</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.103018</td>\n",
" <td>0.377496</td>\n",
" <td>0.464786</td>\n",
" <td>0.470453</td>\n",
" <td>0.400674</td>\n",
" <td>0.388081</td>\n",
" <td>0.408613</td>\n",
" <td>0.528203</td>\n",
" <td>0.540592</td>\n",
" <td>0.444656</td>\n",
" <td>...</td>\n",
" <td>0.000293</td>\n",
" <td>0.000488</td>\n",
" <td>0.000507</td>\n",
" <td>0.000489</td>\n",
" <td>0.000298</td>\n",
" <td>0.000162</td>\n",
" <td>4.025916e-05</td>\n",
" <td>2.583791e-06</td>\n",
" <td>2.853317e-08</td>\n",
" <td>OAF_Pleasant_surprise</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>0.106507</td>\n",
" <td>0.401849</td>\n",
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" <td>0.000315</td>\n",
" <td>0.000180</td>\n",
" <td>6.180123e-05</td>\n",
" <td>2.451167e-05</td>\n",
" <td>2.173154e-05</td>\n",
" <td>OAF_Pleasant_surprise</td>\n",
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]
},
"metadata": {},
"execution_count": 47
}
]
},
{
"cell_type": "code",
"source": [
"print(New_Features_Wav['EMOTIONS'].value_counts())"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Lt9RT45q42Nw",
"outputId": "37154011-f5b2-44a8-add8-611e6b1d21e1"
},
"execution_count": 48,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"OAF_neutral 600\n",
"OAF_Pleasant_surprise 600\n",
"YAF_angry 600\n",
"OAF_happy 600\n",
"YAF_happy 600\n",
"OAF_Sad 600\n",
"YAF_pleasant_surprised 600\n",
"OAF_Fear 600\n",
"OAF_angry 600\n",
"YAF_sad 600\n",
"OAF_disgust 600\n",
"YAF_disgust 600\n",
"YAF_fear 600\n",
"YAF_neutral 600\n",
"Name: EMOTIONS, dtype: int64\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"encoder_label = OneHotEncoder()\n",
"scaler_data = StandardScaler()"
],
"metadata": {
"id": "KuhmC1Mk5IY1"
},
"execution_count": 50,
"outputs": []
},
{
"cell_type": "code",
"source": [
"X = New_Features_Wav.iloc[:,:-1].values\n",
"Y = New_Features_Wav['EMOTIONS'].values\n",
"\n",
"print(X.shape)\n",
"print(Y.shape)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "zcrCV8Wr5RGU",
"outputId": "e7a1ddad-c188-44b1-e943-4bb32b1a2cd3"
},
"execution_count": 51,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(8400, 162)\n",
"(8400,)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"Y = encoder_label.fit_transform(np.array(Y).reshape(-1,1)).toarray()\n",
"print(Y.shape)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "03CzRHLn5fAv",
"outputId": "c92be275-e747-4501-8abd-cfdb4c437b88"
},
"execution_count": 52,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(8400, 14)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"X_train, X_test, y_train, y_test = train_test_split(X, Y, train_size=0.9, random_state=42, shuffle=True)"
],
"metadata": {
"id": "ZYrltt_g5l1l"
},
"execution_count": 53,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print(X_train.shape)\n",
"print(y_train.shape)\n",
"print(X_test.shape)\n",
"print(y_test.shape)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "dPHYMq58504k",
"outputId": "065a4b15-5025-4040-9f08-f543fe15f6c0"
},
"execution_count": 54,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(7560, 162)\n",
"(7560, 14)\n",
"(840, 162)\n",
"(840, 14)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"X_train = scaler_data.fit_transform(X_train)\n",
"X_test = scaler_data.transform(X_test)"
],
"metadata": {
"id": "CTk1xh5B534D"
},
"execution_count": 56,
"outputs": []
},
{
"cell_type": "code",
"source": [
"X_train = np.expand_dims(X_train, axis=2)\n",
"X_test = np.expand_dims(X_test, axis=2)"
],
"metadata": {
"id": "jHZ5UTVh6aOm"
},
"execution_count": 57,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print(X_train.shape)\n",
"print(X_test.shape)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "tMV-uNke63KD",
"outputId": "3f8b9042-fc35-4ed9-fa42-357dff9e45a8"
},
"execution_count": 58,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"(7560, 162, 1)\n",
"(840, 162, 1)\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"# <a name='Model_and_Prediction'></a>\n",
"\n",
"<div style=\"border-radius:10px;\n",
" background-color:#ffffff;\n",
" border-style: solid;\n",
" border-color: #0b0265;\n",
" letter-spacing:0.5px;\">\n",
"\n",
"<center><h3 style=\"padding: 5px 0px; color:#0b0265; font-weight: bold; font-family: Cursive\">\n",
"4. Model and Prediction</h3></center>\n",
"</div>\n",
"\n",
"<a href=\"#toc\" class=\"btn btn-primary btn-sm\" role=\"button\" aria-pressed=\"true\" style=\"color:white\" data-toggle=\"popover\">Back to Table of Contents</a>"
],
"metadata": {
"id": "Qrgdzbe42wYG"
}
},
{
"cell_type": "code",
"source": [
"Model = tf.keras.models.Sequential()\n",
"Model.add(tf.keras.layers.Conv1D(256, kernel_size=5, strides=1, padding='same', activation='relu', input_shape=(X_train.shape[1], 1)))\n",
"Model.add(tf.keras.layers.MaxPooling1D(pool_size=5, strides = 2, padding = 'same'))\n",
"\n",
"Model.add(tf.keras.layers.Conv1D(256, kernel_size=5, strides=1, padding='same', activation='relu'))\n",
"Model.add(tf.keras.layers.MaxPooling1D(pool_size=5, strides = 2, padding = 'same'))\n",
"\n",
"Model.add(tf.keras.layers.Conv1D(128, kernel_size=5, strides=1, padding='same', activation='relu'))\n",
"Model.add(tf.keras.layers.MaxPooling1D(pool_size=5, strides = 2, padding = 'same'))\n",
"Model.add(tf.keras.layers.Dropout(0.2))\n",
"\n",
"Model.add(tf.keras.layers.Conv1D(64, kernel_size=5, strides=1, padding='same', activation='relu'))\n",
"Model.add(tf.keras.layers.MaxPooling1D(pool_size=5, strides = 2, padding = 'same'))\n",
"\n",
"Model.add(tf.keras.layers.Flatten())\n",
"Model.add(tf.keras.layers.Dense(units=32, activation='relu'))\n",
"Model.add(tf.keras.layers.Dropout(0.3))\n",
"\n",
"Model.add(tf.keras.layers.Dense(units=14, activation='softmax'))\n",
"\n",
"Model.summary()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "m-EEz0UR66IN",
"outputId": "9e794527-e76d-47ec-8142-4d9b77305f85"
},
"execution_count": 60,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Model: \"sequential\"\n",
"_________________________________________________________________\n",
" Layer (type) Output Shape Param # \n",
"=================================================================\n",
" conv1d (Conv1D) (None, 162, 256) 1536 \n",
" \n",
" max_pooling1d (MaxPooling1D (None, 81, 256) 0 \n",
" ) \n",
" \n",
" conv1d_1 (Conv1D) (None, 81, 256) 327936 \n",
" \n",
" max_pooling1d_1 (MaxPooling (None, 41, 256) 0 \n",
" 1D) \n",
" \n",
" conv1d_2 (Conv1D) (None, 41, 128) 163968 \n",
" \n",
" max_pooling1d_2 (MaxPooling (None, 21, 128) 0 \n",
" 1D) \n",
" \n",
" dropout (Dropout) (None, 21, 128) 0 \n",
" \n",
" conv1d_3 (Conv1D) (None, 21, 64) 41024 \n",
" \n",
" max_pooling1d_3 (MaxPooling (None, 11, 64) 0 \n",
" 1D) \n",
" \n",
" flatten (Flatten) (None, 704) 0 \n",
" \n",
" dense (Dense) (None, 32) 22560 \n",
" \n",
" dropout_1 (Dropout) (None, 32) 0 \n",
" \n",
" dense_1 (Dense) (None, 14) 462 \n",
" \n",
"=================================================================\n",
"Total params: 557,486\n",
"Trainable params: 557,486\n",
"Non-trainable params: 0\n",
"_________________________________________________________________\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"plot_model(Model, to_file='model.png', show_shapes=True, show_layer_names=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "oTqWEyo8EYYn",
"outputId": "fcc45da4-0afd-4d69-f167-d7684f37898f"
},
"execution_count": 62,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<IPython.core.display.Image object>"
],
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1MTHRrG2bw93dHeHh4Th+/HijdbW1tfD09DRatmLFCnz22Wf46quvmvzCtKaamhoAv1/D1oDtyRjbk+XxnRGiNqhDhw5QqVS4cuWKWdstXrwYd999N44cOWK0vFevXnB3d2/0MuChQ4dQU1OD/v37m7Wfjh07QqvV4ujRo2Zt1xIxMTE4cuQIfv75Z8OyqqoqnDlzxtA9U0Qwd+5c5OXlYfv27Tb/4gBguGZ+fn423/fNsD01xvZkWUxGiNogV1dXdOnSBefOnTNru4bb638eF0Gr1SIpKQnbtm3Dxo0bUV5ejry8PMyYMQMBAQGIj483ez9PP/00Nm3ahMzMTJSXl6Ourg7nzp3Dr7/+CgCIjY2Fn5+fxYYPnzVrFkJCQjBlyhQUFhaipKQEc+fORXV1teFFy+PHj+Odd97BBx98ALVa3Wj+qHfffddQn6Xja9BwzW43foUtsT01xvZkWUxGiNqoMWPGID8/H9XV1YZl//3f/42wsDAUFBQgIiICL730UqPtBg4ciFmzZjVa/sYbb2Dp0qVITk5G+/btMWzYMHTq1Al79uyBm5sbgBvjQjS8K3TPPffg559/xgcffICkpCQAwKhRo3Dq1CkANx5HzZw5E8uWLUO7du0QEBCAxMRElJaWArhxe7moqAg7duy45XEePHgQQ4YMwV133YVDhw7h2LFjCAgIwODBg7Fv3z5DOW9vb3z99dcICgpC3759ERgYiG+//RaffPKJYbwIc8ZisHR8Db777jsEBgbinnvuMTkWW2B7YnuyKkuP6crh4KkBh4M3nyWH7z516pQ4OTnJhg0bLBWeTdXV1cnQoUNl3bp1SofSJGvEd+nSJdFqtfLuu+82Wqf0cPBsT9bVVtuTiTgcPFFbUF1djc8++wynTp0yvLAWFhaG5ORkJCcnt3iGUFurq6vD9u3bUVFRgdjYWKXDacRa8S1atAh9+/ZFQkICgBv/WV+4cAHffPMNfvrpJ4vt53bYnmyrrbcnU9hdMnLw4EF0794dDg4OUKlU8PPzs9ngMab687Ta/v7+TU7DTWQply9fxqhRo9C1a1c888wzhuXz5s3DxIkTERsba/bLh0ras2cPcnJysHv3bpPHtrAla8SXlpaGo0ePYteuXVCr1QCAHTt2IDAwEEOHDsUnn3xikf2Ygu3Jttp6ezKFSsSyA9Zv2bIFMTExVh8Hf9SoUfjss89QWlpq6CbW2oSFheHSpUuGPvV3mokTJwL4vYsv3Z61/n4+//xzfPXVV3j77bctWi9Zxo4dO3D8+HHMmTOn0cueLcH2dGeyt/YEINvu7oy0RtXV1Uaj8FHrYYtrYw/X/6GHHuIXRyv26KOPYt68eRb94rAmtqfWzd7aE2CHj2lao3Xr1qGoqEjpMKgJtrg2vP5ERC3TZpIRU6eafv/996HVatGhQwdMnz7dMNtiZGSk0XwICQkJ0Gg08Pf3Nyx74YUX4ObmBpVKZRgGODExEUlJSSgoKIBKpUJYWFiz4v/666/Ro0cPeHp6QqvVonfv3vjss88AAFOnTjW8fxIaGmoYQOjpp5+Gq6srPD098fHHHwO49TTa77zzDlxdXeHh4YGioiIkJSUhMDAQJ06caFbM1iAmTCvekmtjq+v/6aefQqfTYcmSJVY9X0REbYKl++fYqmvvww8/LACktLTUsGz+/PkCQL788ku5cuWKFBUVydChQ8XNzU1qamoM5eLj48XNzU2OHz8u165dk/z8fImIiBAPDw8pLCw0lIuLixM/Pz+j/aampgoAKS4uNiwbP368hIaGNooxNDRUPD09TTqe7OxsWbRokVy+fFlKSkpk4MCBRt2uxo8fL46OjnL+/Hmj7R5//HH5+OOPDb+/8sor4uzsLFu3bpXS0lJ57bXXxMHBQb777jujc/Tyyy/LihUrJDo6Wv7v//7PpBjN1ZyuvQsXLhSNRiMbNmyQsrIyyc3NlX79+kn79u3l4sWLhnItuTa2uP47d+4UDw8PSU5ONuv42TWeLIntiSyJXXvNdKupphs4OTkZ/vvu0aMHMjMzUVFRYZXppk0xYcIEvPHGG/D29oaPjw/Gjh2LkpISFBcXAwBmzJiBuro6o/jKy8vx3Xff4W9/+xsA86bRfvvtt/Hiiy8iJycHd999t+0O9BaaM614c1n7+o8ZMwbl5eVYsGCBReojImrL2mQy8kd/nmr6ZgYMGABXV1erTDfdHA1dsRompnrwwQfRtWtX/Md//IfhTebNmzcjNjbW8JKSrafRtrSWTiveEq3t+hMR3UnafDJiDmdnZ8OdCFv75JNP8MADD8DX1xfOzs6YM2eO0XqVSoXp06fj559/xpdffgkA+K//+i88++yzhjJ/nEb7j/MfnDlzBlVVVbY7mGay9LTi5lLy+hMR3cmYjPx/er2+WVNXN9e+ffsMcy4UFhZi3Lhx8Pf3x6FDh3DlyhUsW7as0TZTpkyBVqvF2rVrceLECeh0OoSEhBjW/3EabREx+jlw4IBNjqslLD2tuDlsff2JiOh3TkoH0Frs2bMHIoKBAwcaljk5Od328U5z/fDDD4bJoPLy8qDX6/H888+jS5cuAG7cCfkzb29vxMTEYPPmzfDw8MC0adOM1isxjbYlmTOtuKWvja2vPxER/e6OvTNSX1+P0tJS1NbWIjc3F4mJiQgODsaUKVMMZcLCwnD58mVs374der0excXFOHPmTKO6fHx8cOHCBZw+fRoVFRW3/ALT6/X47bffjGamDA4OBgB88cUXuHbtGk6dOnXT9yNmzJiB69evY+fOnXjkkUeM1pkyjXZrZs604i29Nta+/rt372bXXiIiU1m6f461u5IdPHhQevbsKQ4ODgJA/P39ZcmSJZKRkSGurq4CQMLDw6WgoEDWrFkjOp1OAEhISIicPHlSRG507VSr1RIYGChOTk6i0+kkKipKCgoKjPZVUlIiw4cPF61WK507d5aXXnpJZs+eLQAkLCzM0A308OHDEhISIi4uLjJkyBBZtWqVhIaGCoBb/mzbts2wr7lz54qPj494eXnJxIkTZeXKlQJAQkNDjbqbiojce++9Mm/evCbPz/Xr12Xu3LkSHBwsTk5O4uvrK+PHj5f8/HxZtmyZuLi4CADp2LGj1WffbE7X3vr6eklNTZXw8HBRq9Xi7e0t48aNkxMnThiVa+61uXjxotWv/8WLF2XXrl3i4eEhKSkpZh0/u2KSJbE9kSVZs2uv3c5N0xLTp09HdnY2SkpKlA6lWcaMGYOVK1eic+fOSodyS611bprWfP3t4e+H7AfbE1kS56axgoYus/bgj499cnNzodVqW30i0trZ0/UnImrr+AKrHZg7dy5mzJgBEcHTTz+NDRs2KB0SERGRxdxxd0Zee+01rF+/HleuXEHnzp2xdetWpUO6LVdXV9x9990YOXIkFi1ahB49eigdkt2yx+tPRNTW3XHJyNKlS3H9+nWICH755RdMmDBB6ZBuKyUlBXV1dSgsLGzUg4bMY4/Xn4iorbvjkhEiIiJqXZiMEBERkaKYjBAREZGimIwQERGRoqzWtXfLli3WqprsxLlz5wCwLZijYUJDnjOyBLYnsiRrTrhqtRFYiYiIqO2xxgisFk9GiOjOweHGicgC7tzh4ImIiKh1YDJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpiMkJERESKYjJCREREimIyQkRERIpyUjoAIrIP586dw1NPPYW6ujrDstLSUnh4eOCBBx4wKtutWzf84x//sHGERGSvmIwQkUmCgoJw5swZFBQUNFq3d+9eo9/vv/9+W4VFRG0AH9MQkcmefPJJqNXq25aLjY21QTRE1FYwGSEik8XFxaG2tvaWZXr27IkePXrYKCIiaguYjBCRyUJDQ3HPPfdApVI1uV6tVuOpp56ycVREZO+YjBCRWZ588kk4Ojo2ua62thYTJ060cUREZO+YjBCRWR577DHU19c3Wu7g4ICBAweiU6dOtg+KiOwakxEiMktAQAAGDx4MBwfjjw8HBwc8+eSTCkVFRPaMyQgRme2JJ55otExEEB0drUA0RGTvmIwQkdkmTJhg9N6Io6MjRo4ciQ4dOigYFRHZKyYjRGQ2b29v/PWvfzUkJCKCyZMnKxwVEdkrJiNE1CyTJ082vMiqVqsRFRWlcEREZK+YjBBRs4wdOxbOzs4AgEceeQTu7u4KR0RE9orJCBE1i5ubm+FuCB/REFFLqERElA7CVBMnTsTWrVuVDoOIiKhVy8rKwqRJk5QOw1TZdjdr78CBAzFz5kylw2izDhw4gOXLlyMrK0vpUOxKTEwMEhMTMWjQIKVDsam6ujpkZWXh8ccfVzqUVu1ObR+kjJiYGKVDMJvd3RkBgOzsbIUjabu2bNmCmJgY2FGzaBVUKpW9/SdiMdeuXYNWq1U6jFbtTm4fZHt22N6y+c4IEbUIExEiaikmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiOtTH19PdLT0xEZGWlS+alTp8LDwwMqlQpHjx61cnSm27VrFzw9PfGvf/1L6VCIiKiVYzLSipw6dQr3338/Zs2ahaqqKpO2Wbt2LT744AMrR2Y+dg0mIiJT2d2gZ23VsWPHkJycjBkzZqCystLuv8zHjBmDK1euKB0GAKC6uhojRozA/v37lQ6FiIiawDsjrUSfPn2Qk5ODuLg4w+RjplKpVFaKqm1Yt24dioqKlA6DiIhu4o5MRjZs2IABAwZAq9XCzc0NnTp1wuLFiwHceLyQlpaG7t27w9nZGd7e3oiKisKPP/5o2D4zMxNubm5wdXXFjh07MHr0aOh0OgQFBWHTpk2Gct27d4dKpYKDgwP69+9vePQyZ84ceHp6QqvV4sMPPzQrdhFBamoqunXrBmdnZ3h6emL27NktPykW9M033yA4OBgqlQorV64EYPo5e//996HVatGhQwdMnz4dAQEB0Gq1iIyMxKFDhwzlEhISoNFo4O/vb1j2wgsvwM3NDSqVCpcuXQIAJCYmIikpCQUFBVCpVAgLCwMAfPrpp9DpdFiyZIktTgkREd2K2JEJEybIhAkTWlRHenq6AJC33npLSkpK5PLly/KPf/xD4uLiRERk4cKFotFoZMOGDVJWVia5ubnSr18/ad++vVy8eNFQz/z58wWAfPnll3LlyhUpKiqSoUOHipubm9TU1IiISG1trXTq1EmCg4OltrbWKI6ZM2dKenp6kzHed9990qdPnybXzZ8/X1Qqlbz33ntSWloqVVVVkpGRIQDkyJEjLTo3IiJZWVliiWZx9uxZASArVqwwLDPlnImIxMfHi5ubmxw/flyuXbsm+fn5EhERIR4eHlJYWGgoFxcXJ35+fkb7TU1NFQBSXFxsWDZ+/HgJDQ01Krdz507x8PCQ5OTkFh+riAgAycrKskhd1PawfZAt2WF723JH3RnR6/V48803MXz4cLz66qvw8fGBt7c3nn32WURERKC6uhppaWmIjo7G5MmT4enpid69e2P16tW4dOkS1qxZ06jOyMhI6HQ6+Pr6IjY2FpWVlSgsLAQAODo64uWXX0ZhYSG2bdtm2Kaqqgo5OTl45plnzIq/uroa6enpGDlyJGbNmgUvLy+4uLjAx8enZSfGxm51zho4OTkZ7k716NEDmZmZqKiowPr16y0Sw5gxY1BeXo4FCxZYpD4iImq+OyoZyc3NRVlZGR5++GGj5Q1JQ35+Pq5evYoBAwYYrY+IiIBGozF6TNAUjUYD4EbS02Dq1Knw9PTE8uXLDcs2btyIqKgo6HQ6s19txTUAACAASURBVOL/6aefUFVVhREjRpi1XWvW1DlryoABA+Dq6mr0uIyIiNqGOyoZKS8vBwB4eXk1ub6srAwA4O7u3midl5cXKioqzN6nu7s7nnvuOezfvx/ffvstAGDVqlVISEgwu65z584BAHx9fc3eti1wdnZGcXGx0mEQEZGF3VHJyF133QUAhpcb/6whSWkq6SgrK0NQUFCz9puQkAC1Wo309HTs27cPHTt2RGhoqNn1NMyOev369WbFYc/0en2LrgEREbVed1Qy0qlTJ/j4+ODzzz9vcn2vXr3g7u6O77//3mj5oUOHUFNTg/79+zdrv0FBQZg0aRK2bt2KBQsWIDExsVn19OrVCw4ODti7d2+ztrdne/bsgYhg4MCBhmVOTk63fbxDRESt3x2VjDg7O+O1117Dvn37kJCQgPPnz6O+vh4VFRU4fvw4tFotkpKSsG3bNmzcuBHl5eXIy8vDjBkzEBAQgPj4+GbvOykpCbW1tSgtLcWDDz7YrDp8fX0xfvx4bN26FevWrUN5eTlyc3ObfLHW3tXX16O0tBS1tbXIzc1FYmIigoODMWXKFEOZsLAwXL58Gdu3b4der0dxcTHOnDnTqC4fHx9cuHABp0+fRkVFBfR6PXbv3s2uvURErYXS/XnMYYmuvSIiK1eulN69e4tWqxWtViv33nuvZGRkiIhIfX29pKamSnh4uKjVavH29pZx48bJiRMnDNtnZGSIq6urAJDw8HApKCiQNWvWiE6nEwASEhIiJ0+ebLTf4cOHy9q1a5uM6cCBAzJ48GAJCAgQAAJA/P39JTIyUvbu3WsoV1FRIVOnTpV27dqJu7u7DBkyRBYuXCgAJCgoSI4dO9aic2OJrr0rVqwQf39/ASCurq4yduxYs85ZfHy8qNVqCQwMFCcnJ9HpdBIVFSUFBQVG+ykpKZHhw4eLVquVzp07y0svvSSzZ88WABIWFmboBnz48GEJCQkRFxcXGTJkiFy8eFF27dolHh4ekpKS0qJjbQD760pHNsT2QbZkh+1ti0rEfsYdnzhxIgAgOztb4Ujari1btiAmJkbR4einT5+O7OxslJSUKBaDuVQqFbKysjBp0iSlQ6FWiO2DbMkO21v2HfWYhuxHXV2d0iEQEZGNMBkhUtgXX3yBefPmIScnB126dIFKpYJKpcITTzzRqOxDDz0EDw8PODo6omfPnjh8+LACEZuvvr4e6enpiIyMvGkZvV6PpUuXIiwsDBqNBl5eXujVqxdOnz5tKJOcnIwePXpAp9PB2dkZYWFhmDNnDq5evWq1+D7++GMsW7ZMsQSZ7eMGJdqHqfWlpKQYrssff3r16mX2cSjd3hSj8HMis1jqnRG6OUsNB99c8+bNE41GIwCkU6dOkp2drVgs5kAzn9EuXLhQHnnkESkvLzcsCw0NlXbt2gkA2blzZ6Ntdu/eLY8++miL4rWlkydPyuDBgwXATac5EBEZN26cdOvWTQ4ePCh6vV4uXLggY8eOlby8PEOZYcOGSUZGhpSUlEh5eblkZWWJWq2WUaNGWTW+5cuXy7Bhw6S0tLRZ+2D7uLnW3D5MrW/x4sWGd/3++NOzZ89mHYdS7U1BW5iMkBGlkxF71Zw//rfeeku6du0q1dXVRstDQ0Plo48+EgcHBwkMDJSysjKj9fb0ZXP06FGJjo6WjRs3St++fW/6ZbNp0yZRqVSSm5t7y/rGjBnTaJ6nSZMmCQCjeYssHZ+ISEJCggwaNEj0er3Z+2H7aFprbx+m1rd48WLZsGHDbesz9ThEbN/eFHZnzU1D1Fr89NNPWLBgAd58803DYHZ/FBkZicTERJw/fx6vvPKKAhFaRp8+fZCTk4O4uDg4OzvftNyqVavQr18/9O7d+5b17dy5E46OjkbL2rdvDwCGWbGtER8ALFq0CEePHjWa2sFa2D6MKdU+LF2fqccB2La9tQZMRogU8P7770NEMHbs2JuWSUlJQdeuXbF27Vp88cUXt6xPRJCWlmaYXNDb2xtRUVFGc/lkZmbCzc0Nrq6u2LFjB0aPHg2dToegoCBs2rTJqL66ujosXLgQwcHBcHFxwT333IOsrKyWHfRN1NTU4ODBg+jbt2+ztj9//jxcXFzQuXNnC0dmzNvbG8OGDcPy5cut3tuM7eN3ra19NLc+c4/Dlu2tNWAyQqSATz75BN26dYOrq+tNy7i4uODDDz+Eg4MDpk2bhsrKypuWXbRoEebNm4f58+ejqKgI+/btw9mzZzF06FD89ttvAIDnn38eM2fORHV1NTw8PJCVlYWCggJ06dIF06ZNMxrN9tVXX8U777yD9PR0/Prrr3jkkUfw+OOPNxqd2BIuXLiAmpoa/PDDDxg+fDgCAgKg1WrRvXt3ZGRk3PKDuKqqCl999RWmTZtmmHTRmu69916cP38ex44ds+p+2D5+15rax63qmzdvHry9vaHRaNC5c2dERUXhu+++a9Fx2Kq9tQZMRohsrLKyEr/88otJ8xMNGjQIM2fOxOnTp/Hqq682Waa6uhppaWmIjo7G5MmT4enpid69e2P16tW4dOlSkyP0RkZGQqfTwdfXF7GxsaisrERhYSEA4Nq1a8jMzMS4ceMwfvx4eHl54fXXX4darcb69etbdvBNaOiZ4OvriyVLliA/Px+//fYboqKi8OKLL+Kf//znTbddunQpAgICkJKSYvG4mhIeHg4AyMvLs9o+2D6Mtab2cbP6nnrqKXz88cc4e/Ysrl69ik2bNqGwsBDDhg1Dfn5+s4/DFu2ttXBSOgBznTt3Dlu2bFE6jDbrwIEDAMBzbEVFRUUQkVv+1/tHKSkp2LlzJzIyMhATE9NofX5+Pq5evYoBAwYYLY+IiIBGo8GhQ4duWX/Df3gN//meOHECVVVVRt0SXVxc4O/vb3Rb31Ia3hXo2bOnUdfON998E6tWrcKaNWsQFxfXaLtt27Zhy5Yt+Pzzz+Hh4WHxuJrScM0a7iZYA9uHsdbSPm5VX8eOHdGxY0fD7wMHDsT69evRt29fZGRkIDMzs1nHYYv21lrYXTJy8ODBJv/gyLJ4jq3n2rVrAHDbFyYbaLVarF+/HkOGDMEzzzyDZcuWGa0vKysDALi7uzfa1svLq8lZqG+l4Xb/66+/jtdff91oXUBAgFl1maKhzj/Ppq3RaBASEoKCgoJG22zevBlpaWnYs2ePYTZuW3BxcQHw+zW0BrYPY62hfTSnvt69e8PR0REnT54E0LzjsEV7ay3s7jHNhAkTICL8sdJPw0toSsdhbz/maPiAMWdQo0GDBmHWrFk4deoUFi9ebLTOy8sLAJr8UikrK0NQUJBZ8fn6+gIA0tPTGx1nw50zS3J3d0d4eDiOHz/eaF1tbS08PT2Nlq1YsQIbN27EV199ZdNEBLjxEiLw+zW0BrYPY0q3j+bWV19fj/r6ekNSae5xALZpb62F3SUjRPauQ4cOUKlUuHLlilnbLV68GHfffTeOHDlitLxXr15wd3dv9PLgoUOHUFNTg/79+5u1n44dO0Kr1eLo0aNmbdcSMTExOHLkCH7++WfDsqqqKpw5c8bQDVJEMHfuXOTl5WH79u1N/qdvbQ3XzM/Pz2r7YPtoTIn2YU59Dz/8cKNl3333HUQEgwYNMus4/sgW7a21YDJCZGOurq7o0qULzp07Z9Z2Dbfj/zzugVarRVJSErZt24aNGzeivLwceXl5mDFjBgICAhAfH2/2fp5++mls2rQJmZmZKC8vR11dHc6dO4dff/0VABAbGws/Pz+LDTc+a9YshISEYMqUKSgsLERJSQnmzp2L6upqw4uZx48fxzvvvIMPPvgAarW60dDb7777rqE+S8fXoOGamTJORHOxfTSmRPswp77z589j8+bNKCsrg16vx4EDBzB16lQEBwdjxowZZh3HH9mivbUaYkc4Aqv1cQTW5oGZIx4mJCSIWq2Wqqoqw7Jt27ZJaGioAJD27dvLiy++2OS2s2fPbjTCZn19vaSmpkp4eLio1Wrx9vaWcePGyYkTJwxlMjIyxNXVVQBIeHi4FBQUyJo1a0Sn0wkACQkJkZMnT4qIyPXr12Xu3LkSHBwsTk5O4uvrK+PHj5f8/HwRuTGkNQBZuHDhLY/zwIEDMnjwYAkICDAMke3v7y+RkZGyd+9eo7Jnz56Vxx57TLy9vcXZ2Vn+8pe/yO7duw3r8/Lymhxyu+EnNTXVUNYa8YncGJEzMDBQ6uvrb1nvn7F9NK01tw9z6ktKSpLQ0FBxc3MTJycnCQoKkmnTpsmFCxca1Xu74/gjW7W3VoDDwZMxJiPNY+4f/6lTp8TJycmkIaRbo7q6Ohk6dKisW7dO6VCaZI34Ll26JFqtVt59912zt2X7aF1ae3witm1vrQCHgydSQlhYGJKTk5GcnNziGWdtra6uDtu3b0dFRQViY2OVDqcRa8W3aNEi9O3bFwkJCRar82bYPqyntcfXwJbtrTVgMkKkkHnz5mHixImIjY01+2VFJe3Zswc5OTnYvXu3yWNh2JI14ktLS8PRo0exa9cuqNVqi9R5O2wf1tHa4wOUaW9Ku2OSkRMnTuCll15Cz5494eHhAScnJ3h6eqJr164YM2aMVbqkNVd9fT3S09ONBsZpkJOTgy5dujR6mUqj0aBDhw544IEHkJqaitLSUgUiJ3MtWbIECQkJeOutt5QOxWQjRozARx99BH9/f6VDaZKl49uxYweuX7+OPXv2wNvb2yJ1mortw/Jae3xKtjcl3RHJyLp169C7d2/k5uYiLS0NZ8+eRWVlJY4cOYLFixejrKys1Qy3e+rUKdx///2YNWtWk7NCjh8/Hj///DNCQ0Ph6ekJEUF9fT2KioqwZcsWdO7cGXPnzkXPnj2tMk8EWd5DDz2Et99+W+kw6CYeffRRzJs3r1EvFVth+7izKN3elGJ3I7Ca6+DBg4iPj8ewYcPw2Wefwcnp90Pu0qULunTpAi8vL5w6dUrBKG84duwYkpOTMWPGDFRWVpo8mJZKpYKXlxceeOABPPDAAxgzZgxiYmIwZswYnDx5ssnBdFqz6upqjBgxAvv377frfRARkWna/J2RlJQU1NXV4a233jJKRP7o4YcfxosvvmjjyBrr06cPcnJyEBcXZ/JQ0E2ZMGECpkyZgqKiIqxevdqCEdrGunXrUFRUZPf7ICIi07TpZKSmpgZffvkl2rVrh7/85S8mbyciSEtLQ/fu3eHs7Axvb29ERUUZTQKVmZkJNzc3uLq6YseOHRg9ejR0Oh2CgoKwadMmQ7nu3btDpVLBwcEB/fv3Nzx6mTNnDjw9PaHVavHhhx9a7JgbTJkyBQCwe/dui9f9Z6acr4SEBGg0GqPntC+88ALc3NygUqkM8zUkJiYiKSkJBQUFUKlUCAsLw/vvvw+tVosOHTpg+vTphqm3IyMjjSb5ask+AODTTz+FTqfDkiVLrHq+iIjoT5TtWmwec8cZOXnypACQgQMHmrWfhQsXikajkQ0bNkhZWZnk5uZKv379pH379nLx4kVDufnz5wsA+fLLL+XKlStSVFQkQ4cOFTc3N6mpqRERkdraWunUqZMEBwdLbW2t0X5mzpwp6enpTcZw3333SZ8+fW4aY2hoqHh6et50fXl5uQCQjh07mnPozRpnxNTzFRcXJ35+fkbbpqamCgApLi42LBs/fryEhoYalYuPjxc3Nzc5fvy4XLt2TfLz8yUiIkI8PDyksLDQIvvYuXOneHh4SHJyslnHL2KX/frJhtg+yJbssL217XFGysvLATQ9W+XNVFdXIy0tDdHR0Zg8eTI8PT3Ru3dvrF69GpcuXcKaNWsabRMZGQmdTgdfX1/ExsaisrIShYWFAABHR0e8/PLLKCwsxLZt2wzbVFVVIScnB88880wLj7JpHh4eUKlUZs/Iaa7mnK/mcnJyMtx96dGjBzIzM1FRUYH169dbpP4xY8agvLwcCxYssEh9RERkmjadjDQkIU31SrmZ/Px8XL16FQMGDDBaHhERAY1GY/RYoCkajQYAoNfrDcumTp0KT09PLF++3LBs48aNiIqKgk6nMzk2czS8AGut+hu09Hy1xIABA+Dq6mr0OIiIiOxPm05GOnXqBK1Wi5MnT5q8TVlZGYCm76Z4eXk1606Du7s7nnvuOezfvx/ffvstAGDVqlVWHVmv4Zjvvvtuq+0DsM75MoezszOKi4utug8iIrKuNp2MODs74+GHH8alS5fw73//+6blLl++jKlTpwK48QUKoMkv0bKyMgQFBTUrloSEBKjVaqSnp2Pfvn3o2LEjQkNDm1WXKT799FMAwOjRo622D8B658sUer3e6vsgIiLra9PJCHBjfH9nZ2fMmjUL1dXVTZb53//9X0O33169esHd3b3RgGGHDh1CTU0N+vfv36w4goKCMGnSJGzduhULFixAYmJis+oxxcWLF5Geno6goCCrvZPSwJzz5eTkZPT4qqX27NkDEcHAgQOttg8iIrK+Np+M9O3bFx999BH+93//F0OHDsWuXbtw5coV6PV6/PLLL/jggw/w7LPPGsb/12q1SEpKwrZt27Bx40aUl5cjLy8PM2bMQEBAAOLj45sdS1JSEmpra1FaWooHH3ywxccmIrh69Srq6+shIiguLkZWVhYGDx4MR0dHbN++3ervjJhzvsLCwnD58mVs374der0excXFOHPmTKM6fXx8cOHCBZw+fRoVFRWG5KK+vh6lpaWora1Fbm4uEhMTERwcbOjG3NJ97N69m117iYiUoGxvHvOY27X3jwoLC+WVV16R3r17i7u7uzg6OoqXl5fce++98uyzz8q///1vQ9n6+npJTU2V8PBwUavV4u3tLePGjZMTJ04YymRkZIirq6sAkPDwcCkoKJA1a9aITqcTABISEiInT55sFMfw4cNl7dq1TcZ44MABGTx4sAQEBAgAASD+/v4SGRkpe/fuFRGRjz/+WO655x5xdXUVjUYjDg4OAkBUKpV4eXnJX/7yF0lOTpaSkpJmnafmdO015XyJiJSUlMjw4cNFq9VK586d5aWXXpLZs2cLAAkLCzN00T18+LCEhISIi4uLDBkyRC5evCjx8fGiVqslMDBQnJycRKfTSVRUlBQUFFhsH7t27RIPDw9JSUkx+7zB/rrSkQ2xfZAt2WF726ISMXHM8VZg4sSJAIDs7GyFI2m7tmzZgpiYGJOHoreV6dOnIzs7GyUlJUqH0iSVSoWsrCxMmjRJ6VCoFWL7IFuyw/aW3eYf01DbUVdXp3QIRERkBUxGiIiISFFMRqjVe+2117B+/XpcuXIFnTt3xtatW5UOiYiILKjpaWyJWpGlS5di6dKlSodBRERWwjsjREREpCgmI0RERKQoJiNERESkKCYjREREpCi7e4H14MGDhsHPyPLOnTsHADzHzZCens4B+eim2D6Ibs6uRmBNS0vDgQMHlA6DiP6/ixcv4siRI1afHZqIzDNr1iwMGjRI6TBMlW1XyQgRtS6tdfoAIrIrHA6eiIiIlMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTlpHQARGQf9Ho9rl69arSssrISAFBaWmq0XKVSwcvLy2axEZF9YzJCRCa5fPkyAgMDUVdX12idj4+P0e/Dhw/HV199ZavQiMjO8TENEZnEz88P999/Pxwcbv2xoVKp8Nhjj9koKiJqC5iMEJHJnnjiiduWcXR0RHR0tA2iIaK2gskIEZls/PjxcHK6+dNdR0dHjBo1Cu3atbNhVERk75iMEJHJdDodRo8efdOEREQwefJkG0dFRPaOyQgRmWXy5MlNvsQKABqNBn//+99tHBER2TsmI0Rklr///e9wdXVttFytVmPcuHFwc3NTICoismdMRojILFqtFtHR0VCr1UbL9Xo94uLiFIqKiOwZkxEiMtvjjz8OvV5vtEyn0+Gvf/2rQhERkT1jMkJEZhs5cqTRQGdqtRqPPfYYNBqNglERkb1iMkJEZnNycsJjjz1meFSj1+vx+OOPKxwVEdkrJiNE1CyPPfaY4VGNn58fhgwZonBERGSvmIwQUbNERkYiMDAQAPDkk0/edph4IqKbMXmivC1btlgzDiKyQxERETh//jzatWvHzwgiMtKxY0cMGjTIpLIqERGTCqpULQqKiIiI7hwTJkxAdna2KUWzTb4zAgBZWVmYNGlS86KiO97EiRMBwNTGSbhxRzImJgYm/s+giK1bt2LChAlKh0EWYA/tjexDw+e9qfiQl4hahIkIEbUUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTEYW8++676NChA1QqFVavXm1YvmvXLnh6euJf//qX1WOor69Heno6IiMjTSo/depUeHh4QKVS4ejRo1aO7uZseY6IiMj6mIwo5JVXXsH+/fsbLbdV//5Tp07h/vvvx6xZs1BVVWXSNmvXrsUHH3xg5chuj2MgEBG1LWYNekbWN2bMGFy5csWq+zh27BiSk5MxY8YMVFZW2t2Xuy3Okamqq6sxYsSIJhNLIiIyDe+MtHEiguzsbKxZs8awrE+fPsjJyUFcXBycnZ3Nqo/TAhhbt24dioqKlA6DiMiuWSUZWb58Odzc3ODg4ID+/fvDz88ParUabm5u6NevH4YOHYqOHTtCq9XCy8sLc+bMMdr+66+/Ro8ePeDp6QmtVovevXvjs88+AwB8+OGHcHd3h0qlgre3N7Zv347vv/8eISEhcHR0xOOPP25WrO+//z60Wi06dOiA6dOnIyAgAFqtFpGRkTh06JBRWRFBWloaunfvDmdnZ3h7eyMqKgo//vhjs8r92TfffIPg4GCoVCqsXLkSAJCZmQk3Nze4urpix44dGD16NHQ6HYKCgrBp0yaj7evq6rB06VJ069YNLi4uaN++PTp37oylS5c2axh/EUFqaiq6desGZ2dneHp6Yvbs2WbXY0ktOUemXuuEhARoNBr4+/sblr3wwgtwc3ODSqXCpUuXAACJiYlISkpCQUEBVCoVwsLCAACffvopdDodlixZYotTQkRk/8REACQrK8vU4vLGG28IADl06JBUVlbKpUuXZNSoUQJAPvnkEykuLpbKykpJSEgQAHL06FHDttnZ2bJo0SK5fPmylJSUyMCBA6Vdu3aG9cePHxdXV1d56qmnDMvmzZsna9euNTm+P4qPjxc3Nzc5fvy4XLt2TfLz8yUiIkI8PDyksLDQUG7hwoWi0Whkw4YNUlZWJrm5udKvXz9p3769XLx40exyp06dEgCyatUqw7KzZ88KAFmxYoVh2fz58wWAfPnll3LlyhUpKiqSoUOHipubm9TU1BjKLVmyRBwdHWXHjh1SVVUlP/zwg/j5+ckDDzxw02O/7777pE+fPk2umz9/vqhUKnnvvfektLRUqqqqJCMjQwDIkSNHzDvJIjJhwgSZMGGC2dv9WUvOkanXOi4uTvz8/Iz2m5qaKgCkuLjYsGz8+PESGhpqVG7nzp3i4eEhycnJLT7WrKwsMePPlKhF2N7IUsz8vN9i9cc0PXr0gKurK9q1a4fHHnsMABAcHIz27dvD1dUVkydPBgCjuwYTJkzAG2+8AW9vb/j4+GDs2LEoKSlBcXExAKB79+5IT0/Hf/7nf+Kjjz7Cpk2bcP36dTz77LPNjtPJyclwJ6NHjx7IzMxERUUF1q9fD+DGuwFpaWmIjo7G5MmT4enpid69e2P16tW4dOmS4TGIqeWaIzIyEjqdDr6+voiNjUVlZSUKCwsN67dv347+/ftj7NixcHFxQb9+/fDoo49i3759qKmpMWtf1dXVSE9Px8iRIzFr1ix4eXnBxcUFPj4+zY7fFm53joDbX+uWGjNmDMrLy7FgwQKL1EdE1NbZ9AVWjUYDAKitrTUsU6vVAAC9Xn/T7RrK1NXVGZY999xz+J//+R9Mnz4dI0eOxNatWy0a64ABA+Dq6mpIkvLz83H16lUMGDDAqFxERAQ0Go3hNr+p5Vqq4Vz+8bxdu3YNWq3WqFxdXR3UajUcHR3Nqv+nn35CVVUVRowY0fJgFdLUOWrKn681ERHZVqt8gfWTTz7BAw88AF9fXzg7Ozd6p6TBkiVLcPXqVau9QOjs7Gy4G1NWVgYAcHd3b1TOy8sLFRUVZpWzhr/97W/44YcfsGPHDlRXV+P777/H9u3b8fe//93sZOTcuXMAAF9fX2uE2ur88VoTEZFttbpkpLCwEOPGjYO/vz8OHTqEK1euYNmyZY3K6fV6vPzyy0hLS8OBAweQkpJi0Tj0ej3KysoQFBQE4EYiAaDJZKI55axh0aJFePDBBzFlyhTodDpER0dj0qRJzRobpOEOy/Xr1y0dZqvz52tNRES21erGGcnLy4Ner8fzzz+PLl26AGi6O+lLL72EadOmITo6GufPn8fixYvx0EMPYdCgQRaJY8+ePRARDBw4EADQq1cvuLu74/vvvzcqd+jQIdTU1KB///5mlbOG/Px8FBQUoLi4GE5OLbu0vXr1goODA/bu3YsZM2ZYKMLW6c/XGrjxXsntHu8QEZFltLo7I8HBwQCAL774AteuXcOpU6cavWeRkZGBwMBAREdHAwCWLl2KHj16IC4uDuXl5c3ab319PUpLS1FbW4vc3FwkJiYiODgYU6ZMAXDjTkFSUhK2bduGjRs3ory8HHl5eZgxYwYCAgIQHx9vVjlrePHFFxEcHIyrV6+2uC5fX1+MHz8eW7duxbp161BeXo7c3NwWs0nW0gAAIABJREFUvYDbWtzuWgNAWFgYLl++jO3bt0Ov16O4uBhnzpxpVJePjw8uXLiA06dPo6KiAnq9Hrt372bXXiIic5ja7wZmdO1dvny5uLq6CgDp1KmTfP311/L222+Lp6enABA/Pz/56KOPZPPmzeLn5ycAxNvbWzZt2iQiInPnzhUfHx/x8vKSiRMnysqVKwWAhIaGSt++fUWlUomPj4/s379fRERmzpwpDg4OAkA8PT3l+++/N/WwRORGd0+1Wi2BgYHi5OQkOp1OoqKipKCgwKhcfX29pKamSnh4uKjVavH29pZx48bJiRMnzC733nvvGY7dzc1NoqOjZcWKFeLv7y8AxNXVVcaOHSsZGRmGcxkeHi4FBQWyZs0a0el0AkBCQkLk5MmTIiLy1VdfSbt27QSA4UetVkv37t0lJyfHsO8DBw7I4MGDJSAgwFDO399fIiMjZe/evYZyFRUVMnXqVGnXrp24u7vLkCFDZOHChQJAgoKC5NixY2adZ0t07W3pOTL1WpeUlMjw4cNFq9VK586d5aWXXpLZs2cLAAkLCzN0Az58+LCEhISIi4uLDBkyRC5evCi7du0SDw8PSUlJadGxirCrJdkW2xtZirlde1Uipo0FrlKpkJWV1azBs1q76dOnIzs7GyUlJUqH0iKZmZk4deoU0tPTDctqamrw6quvIjMzE6WlpXBxcVEsvokTJwIAsrOzFYvB3q71li1bEBMTY3dD9pN9YnsjSzHz8z671b0zopQ/dhu2RxcvXkRCQkKj2XQ1Gg2Cg4Oh1+uh1+sVTUZaC3u/1kREbU2re2fEEn788UeoVKrb/sTGxiodqsW4uLhArVZj3bp1+O2336DX63HhwgWsXbsWCxcuRGxsLHQ6ndJhko198cUXmDdvHnJyctClSxdD23/iiScalX3ooYfg4eEBR0dH9OzZE4cPH1YgYvPV19cjPT0dkZGRNy2j1+uxdOlShIWFQaPRwMvLC7169cLp06cNZZKTk9GjRw/odDo4OzsjLCwMc+bMafY7WKbWl5KS0uTnU69evcw+jo8//hjLli1TLOFu6+3tn//8JyIiIuDh4YGQkBA8/fTTuHjxYpNlTWmXprhj2pGpD3Rg5nDw9mLevHmi0WgM77dkZ2crHVKz7du3T0aOHCk6nU4cHR3F09NTIiMjJSMjQ/R6vdLhWWw4+Oayx2vdkmf4CxculEceeUTKy8sNy0JDQw3vFe3cubPRNrt375ZHH3202fHa2smTJ2Xw4MEC4KbTGoiIjBs3Trp16yYHDx4UvV4vFy5ckLFjx0peXp6hzLBhwyQjI0NKSkqkvLxcsrKyRK1Wy6hRo5oVm6n1LV682Og9r4afnj17Nus4li9fLsOGDZPS0lKzY2Z7u7nNmzcLAFm2bJmUlZXJkSNHpEuXLtK3b99Gn6+mtktT2GM7EjH/nZE7Phkh21E6GbFHzf1yeOutt6Rr165SXV1ttDw0NFQ++ugj+X/s3XlcU1f6P/BPgIQkQAK4gSLI4oZScWsVtYq2Oh1GRepCxba21bq0RZRaQdRRRFvFAl8V9OtS7NSOAuJgx2rttB1rVdzqhvitC62CIoIIsgQlwPP7wx+pMaAJBC7L8369+IObc8957s0Jebj33HNMTEyoU6dOVFhYqPV6c/pyOH/+PPn5+dHOnTvJ09Oz1j/6u3btIpFIRBcvXnxmfT4+PlRRUaG1bfLkyQRAa90ifelb38qVK+mrr756bn36HgcRUWBgIA0ePNjgf0K4v9XO29ubOnbsSFVVVZpt1Q9XHD16VLNN336pr+bYj4ia4No0jLHGdf36dSxduhQrVqzQWR4AeLx+T1BQEG7fvo2PP/5YgAiNo0+fPkhOTkZAQADMzc1rLbdp0yb069cPHh4ez6xv//79OjMVt23bFgCgUqkMjs/Y9el7HMDjCRDPnz+PmJgYg9sxVGvpb1lZWbC3t9ea96pz584AoPXYv779Ul+tpR9xMsJYC7N+/XoQEcaNG1drmYiICHTr1g3btm3DDz/88Mz6iAhRUVGaxQVtbGzg6+urtZZPXFwcLCwsIJfLsW/fPrz22mtQKBRwcHDArl27tOqrrKzEsmXL4OjoCJlMhhdeeAEJCQn1O+halJeX48SJE/D09KzT/rdv34ZMJoOzs7NR4qlrfYYeh42NDYYPH46YmJgGfzKmtfQ3FxcXnaVHqseLVE/Q2VhaYj/iZISxFubbb79F9+7dIZfLay0jk8mwY8cOmJiYYObMmSgtLa217PLlyxEaGoqwsDDk5ubiyJEjyMrKwrBhw3D37l0AwNy5czF//nyUlZXBysoKCQkJyMjIgIuLC2bOnKk1m21ISAjWrl2L6Oho3LlzB2PHjsXUqVN1Zi02huzsbJSXl+PXX3+Ft7c37O3tIZVK0bNnT8TGxj7zD6xKpcJPP/2EmTNnahZdrI9n1RcaGgobGxtIJBI4OzvD19cXp0+frtdx9O3bF7dv38aFCxfqHfuztJb+tnjxYuTk5GDDhg0oLi5Geno6YmJiMGbMGK3ZmxtaS+1HPGaENRoeM2I4Q+/hl5SUkEgkorFjx9b4uqurK/3xxx+a34ODgwkAffjhh0Skew9fpVKRpaUl+fv7a9Vz6tQpAkDh4eGabWFhYQRAa9xAbGwsAaDr168TEVFZWRnJ5XKt+lQqFZmbm9PcuXP1Ps6nvfTSSzXem09LSyMA9Oqrr9KxY8coPz+fCgsLKSQkhADQzp07a60zLCyMunXrpjUgsz5qqy8zM5POnj1LxcXF9OjRI0pNTaW+ffuSTCajS5cu1fk4vvjiCwJA//jHP/SOkfvbsy1ZskRrcKiDgwNlZWXVWr62flkfzaEfERk+ZsSgeUaio6MFnbCKNW8nTpwA8OdkOOz5qldP1ldubi6I6Jn/pT4pIiIC+/fvR2xsLKZMmaLzenp6OkpKSjBgwACt7QMHDoREItFZquFp1f+5Vf+neuXKFahUKq3HDWUyGezs7LQuwxtL9T37Xr16aT1iuWLFCmzatAlbtmxBQECAzn579+5FYmIivv/+e1hZWdU7jmfV17lzZ83YAwAYNGgQ4uPj4enpidjYWMTFxdXpOKr7QPXVhIbQmvpbWFgYtm3bhh9//BEvvfQScnNzERISgsGDB+P48eNa72FDaan9CODbNIy1KA8fPgQAvQfOSaVSxMfHQyQS4d1330VZWZnW64WFhQAAS0tLnX2tra1rXJ36Waovzy9ZskRrLoSbN2/WaTDe89jb2wMA7t27p7VdIpHAyckJGRkZOvvs3r0bn332GQ4fPowuXbrUO4a61Ofh4QFTU1NcvXoVQN2Oo3qCw+o+0RBaS3+7c+cO1qxZg/fffx8jR46EhYUFnJ2dsXXrVmRnZyMyMtKguOqiJfcjwMBVe+fPn98ip4NnjaMpTAff3FRPz62v6j8chkxWNHjwYCxYsADr1q3DypUrNYtVAo+/AADU+CVQWFgIBwcHvdsBHi/ACDy+yhoUFGTQvnVhaWmJrl274vLlyzqvVVRUQKlUam3bsGEDDh06hJ9++qnGL0RD1bW+qqoqVFVVab7kDT0O4PFgRQANOutya+lv165dQ2VlJTp27Ki1XaFQwNbWFunp6XWuWx8tvR8BfGWEsRalffv2EIlEePDggUH7rVy5Ej169MC5c+e0tvfu3RuWlpY6g/1OnjyJ8vJy9O/f36B2OnfuDKlUqrNsQUOaMmUKzp07h99//12zTaVS4ebNm5rHG4kIixYtQlpaGlJSUuqdiBhS35gxY3S2nT59GkSEwYMHG3QcT6ruAx06dKjPoTxTa+lv1UnQnTt3tLYXFxfj/v37DXaLprX0I4CTEcZaFLlcDhcXF4PHmlRfPn96PgOpVIrg4GDs3bsXO3fuRFFREdLS0jBnzhzY29tj1qxZBrfzzjvvYNeuXYiLi0NRUREqKytx69YtzR96f39/dOjQwWjTgy9YsABOTk6YPn06MjMzkZ+fj0WLFqGsrAwhISEAgMuXL2Pt2rXYunUrxGKxzpTa69at09SnT3yG1Hf79m3s3r0bhYWFUKvVSE1NxYwZM+Do6Ig5c+YYdBxPqu4D+swnUVetpb85OzvD29sbW7duxZEjR1BWVoasrCxNPO+9955BcenbbmvpRwD4aRrWePhpGsPVZUbMwMBAEovFpFKpNNv27t1Lrq6uBIDatm2reZrhaQsXLtSZEbOqqooiIyOpa9euJBaLycbGhiZMmEBXrlzRlImNjSW5XE4AqGvXrpSRkUFbtmwhhUJBAMjJyYmuXr1KRESPHj2iRYsWkaOjI5mZmVG7du3o9ddfp/T0dCJ6PFU1AFq2bNkzjzM1NZWGDBlC9vb2mqcb7OzsyMvLi37++WetsllZWfTGG2+QjY0NmZub04svvkgHDx7UvF79lEFtP5GRkZqy+sRnSH3BwcHk6upKFhYWZGZmRg4ODjRz5kzKzs7Wqfd5x/EkHx8f6tSpk9aMoc/D/a129+7do6CgIHJzcyNzc3OytLSkIUOG0L/+9S+tcvr2y5bcj4h4OnjWhHEyYri6fDlcu3aNzMzM9JoauimqrKykYcOG0fbt24UOpUZNPT6ix1+cUqmU1q1bZ9B+3N9afruGqGs/IuLp4Blr9dzc3BAeHo7w8PA6rzgrlMrKSqSkpKC4uLhJrqrd1OOrtnz5cnh6eiIwMLDB2+L+1nzaNVRj9qMGTUaeXkZ66dKlzywfFRUFkUgEExMT9OjRA0eOHGmwWEQiEcRiMTp16oSAgAD83//9n9Haetq6des0A702b96s2X7gwAEolUr8+9//brC2qz1rOeuazo1IJIJEIkH79u0xYsQIREZGoqCgoMHjZMYRGhqKSZMmwd/f3+DBhUI6fPgwkpOTcfDgQb3nrmhMTT0+4PHf0fPnz+PAgQMQi8WN0ib3t+bRriEavR/pew0F9bhNU33v0M7OjsrLy2ssU1FRQU5OTgSARo0aVad29I1FqVQS0ePZA7/55htydHQkS0tL+u233xqs3WvXrhEA2rRpk2bb/v37SaFQ0DfffNNg7RLpv5z1k+emqqqKCgoK6L///S9Nnz6dRCIR2dvb0+nTp+scB9+mMVx9lnQnIjp06BAtWrTIiBGxpiwlJYVWr16ts8qrvri/MaL69yOiJnybpn///sjJyUFKSkqNrycnJ6NTp06NFQ4AwMLCAmPHjsX//M//oKSkBBs2bGjU9n18fPDgwQOMHTu2wdq4cOECQkJCMGfOHIMWCxOJRLC2tsaIESMQHx+PxMRE3L17VxNzc1VWVlbj1aHm1oa+Ro8ejc8++0zoMFgjGT9+PEJDQ3WeUmks3N9aBiH6UaMlI3PnzgXwePnimkRFRSE4OLixwtHy4osvAgAuXbokSPvGQkRISkrCli1bNNuMtZz1xIkTMX36dOTm5mrdamputm/frrPyZnNsgzHGWpJGS0ZGjhyJnj174r///S+uXLmi9dqxY8egUqkwevToGvf95Zdf4O7uDqVSCalUCg8PDxw6dAgAsGPHDlhaWkIkEsHGxgYpKSk4c+YMnJycYGpqiqlTpz43toqKCgDaUxqTHstYG1LuaUePHoWjoyNEIhE2btwIwPBlsVevXo3u3btDJpOhbdu2cHZ2xurVqxtsltzp06cDAA4ePNgg9ddEn/MbGBgIiUQCOzs7zbYPPvgAFhYWEIlEmqmPg4KCEBwcjIyMDIhEIri5uWH9+vWQSqVo3749Zs+erVnF0svLS2sdjPq0AQDfffcdFAoFVq1a1aDnizHGmqNGfZpm9uzZAKDzn/Xnn3+OBQsW1Lrf3bt3MWXKFNy4cQPZ2dmwtLTULOYzffp0nD59GnK5HOPHj4evry8GDBiAgIAAbNmyBf/85z+fG1f1QNk+ffpotumzjLUh5Z42dOhQHD9+XGubIctir1mzBsuWLUNkZCTu37+P77//Hg8fPoS1tbVmSmVjq77N8+TMfQ1Nn/O7fv16nQQsNjYWK1as0NoWExODsWPHwtXVFUSE69evIzAwENOnT4dKpcK8efNw48YNnD17FhUVFXj11VeRlZVV7zaAP6fLrqqqMt7JYYyxFqJRk5G3334bFhYW+PLLLzULJP3+++84ffr0M69gTJw4EX//+99hY2MDW1tbjBs3Dvn5+cjLywMA9OzZE9HR0fjyyy/x9ddfY9euXXj06NFzZ8UrLS1FcnIyPv74Y7Rv3x7z5s0D8Pief1RUFPz8/DBt2jQolUp4eHhg8+bNuHfvnuY2iL7l6sLLywsKhQLt2rWDv78/SktLkZmZqXk9JSUF/fv3x7hx4yCTydCvXz+MHz8eR44c0awlYGxWVlYQiUQGL1ZVVw15fp9mZmamufri7u6OuLg4FBcXIz4+3ij1+/j4oKio6LlPlDHGWGvUqMmIUqnE1KlTUVBQgN27dwN4vIDR3LlzNUs/66P6MaMnF2d6//33MXHiRMyePRuJiYlYu3Ztrfs/ePAAIpEISqUS8+bNw1//+lecOnVKM4BW32Ws67vctb6eXhYbeLyCIhFplausrIRYLG6wQUelpaUgIigUigap/2mNdX5rMmDAAMjl8gZZ1p4xxpi2Rp/0rHog6+bNm1FYWIikpCTN7ZvafPvttxgxYgTatWsHc3NzfPLJJzWWW7VqFUpKSp47eFCpVIKIUFFRgVu3buGLL76Ak5OT5nV9l7E29nLXhvjrX/+KX3/9Ffv27UNZWRnOnDmDlJQU/O1vf2uwZKR6GeoePXo0SP1PE/L8Ao/HEFVffWOMMdZwGj0Z8fT0xKBBg3Dq1CnMmjULkyZNgo2NTa3lMzMzMWHCBNjZ2eHkyZN48OAB1qxZo1NOrVZj3rx5iIqKQmpqKiIiIuoco77LWBt7uWtDLF++HCNHjsT06dOhUCjg5+eHyZMnY+vWrQ3W5nfffQcAeO211xqsjScJeX7VanWDt8EYY+wxMyEanTt3Lk6cOIE9e/bg2rVrzyyblpYGtVqNuXPnwsXFBcDjOTCe9tFHH2HmzJnw8/PD7du3sXLlSowePVpr6WR96buMtbGXuzZEeno6MjIykJeXBzOzhn8bc3JyEB0dDQcHB7z77rsN3h5g2Pk1MzPTuo1VX4cPHwYRYdCgQQ3WBmOMsccEWZtm8uTJaNu2LSZMmKBJMGrj6OgIAPjhhx/w8OFDXLt2TWesQGxsLDp16gQ/Pz8AwOrVq+Hu7o6AgAAUFRUZHJ++y1gbe7lrQ3z44YdwdHQ0+loQRISSkhJUVVWBiJCXl4eEhAQMGTIEpqamSElJabQxI4acXzc3N9y/fx8pKSlQq9XIy8vDzZs3deq0tbVFdnY2bty4geLiYk1yUVVVhYKCAlRUVODixYsICgqCo6Oj5nHm+rZx8OBBfrSXMcZqo+9crajDdPDPWkb6k08+oePHj2t+X7JkCdnZ2REAMjExIXd3d/rll1+IiGjRokVka2tL1tbWNGnSJNq4cSMBIFdXV/L09CSRSES2traa+ubPn08mJiYEgJRKJZ05c4aOHTtG3bp10yy9bG9vT5MmTao1dn2Wsda33Oeff04dOnQgAGRhYUF+fn60YcMGzfHK5XIaN26cQcti//TTT9SmTRut5aTFYjH17NmTkpOTNW3rs5z1N998Qy+88ALJ5XKSSCSacycSicja2ppefPFFCg8Pp/z8fIPe/6fVZTp4fd+H/Px88vb2JqlUSs7OzvTRRx/RwoULCQC5ublRZmYmERGdPXuWnJycSCaT0dChQyknJ4dmzZpFYrGYOnXqRGZmZqRQKMjX15cyMjKM1saBAwfIysqKIiIiDDr++k7PzZghuL8xYzF0OngR0VOPZNRCJBIhISGhwSbUYoaJi4vDtWvXEB0drdlWXl6OkJAQxMXFoaCgADKZTMAIdU2aNAkAkJSUJHAk2mbPno2kpCTk5+cLHYqOxMRETJkyRefJKcYaAvc3ZiwG/r1PEmTMCKufnJwcBAYG4vz581rbJRIJHB0doVaroVarm1wy0pQ9+Zg4Y4yxxiXImBFWPzKZDGKxGNu3b8fdu3ehVquRnZ2Nbdu2YdmyZfD392+0cR2MMcZYfXEy0gwplUp8//33uHTpErp16waZTAZ3d3fEx8fjs88+w5dffil0iM3G4sWLER8fjwcPHsDZ2Rl79uwROiTGGGt1+DZNMzVs2DD85z//ETqMZm/16tVYvXq10GEwxlirxldGGGOMMSYoTkYYY4wxJihORhhjjDEmKE5GGGOMMSYoTkYYY4wxJiiDZmBljDHGGNPHxIkTjT8Da0JCQt0jYoy1SKmpqYiJieG/D4wxHZ07d9a7rN5XRhhj7Gm8lgljzAiSeMwIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBMXJCGOMMcYExckIY4wxxgTFyQhjjDHGBGUmdACMseYhLy8P//rXv7S2nTlzBgCwZcsWre1WVlZ44403Gi02xljzJiIiEjoIxljT9+jRI7Rv3x4lJSUwNTUFAFT/+RCJRJpyarUab7/9Nnbs2CFEmIyx5ieJb9MwxvRibm6OiRMnwszMDGq1Gmq1GhUVFaioqND8rlarAQBTp04VOFrGWHPCyQhjTG9Tp05FeXn5M8tYW1tj5MiRjRQRY6wl4GSEMaY3b29vtGvXrtbXxWIxpk2bBjMzHo7GGNMfJyOMMb2ZmJggICAAYrG4xtfVajUPXGWMGYyTEcaYQd544w3N2JCndezYEYMHD27kiBhjzR0nI4wxg7z44otwcnLS2S6RSPD2229rPVnDGGP64GSEMWawN998U+dWTXl5Od+iYYzVCScjjDGDBQQE6NyqcXNzg4eHh0ARMcaaM05GGGMG69GjB9zd3TW3ZMRiMd555x2Bo2KMNVecjDDG6uStt97SzMRaUVHBt2gYY3XGyQhjrE7eeOMNVFZWAgD69esHZ2dngSNijDVXnIwwxurE0dERL730EgDg7bffFjgaxlhz1iSnSYyKikJqaqrQYTDGnuPRo0cQiUT4/vvvceTIEaHDYYw9x4IFC5rkXEBN8spIamoqTpw4IXQY7P87ceIEvx8GunXrFvbs2SN0GA3OwcEBHTp0gFQqFTqUFos/f8xY9uzZg6ysLKHDqFGTvDICAIMGDUJSUpLQYTAAkyZNAgB+PwyQmJiIKVOmtIpzdv36dbi5uQkdRovFnz9mLE15QsImeWWEMdZ8cCLCGKsvTkYYY4wxJihORhhjjDEmKE5GGGOMMSYoTkYYY4wxJihORhpJVVUVoqOj4eXlpVf5GTNmwMrKCiKRCOfPn2+0dhvSgQMHoFQq8e9//1voUBhjjDUhnIw0gmvXruHll1/GggULoFKp9Npn27Zt2Lp1a6O325CISOgQGGOMNUFNdp6RluLChQsIDw/HnDlzUFpa2mhfyEK1+yw+Pj548OCB0GEAAMrKyjBq1CgcP35c6FAYY6zV4ysjDaxPnz5ITk5GQEAAzM3NDdq3PhPU1Kfd1mD79u3Izc0VOgzGGGNoYcnIV199hQEDBkAqlcLCwgJdunTBypUrATy+RRAVFYWePXvC3NwcNjY28PX1xW+//abZPy4uDhYWFpDL5di3bx9ee+01KBQKODg4YNeuXZpyPXv2hEgkgomJCfr376+5BfLJJ59AqVRCKpVix44dBsVORIiMjET37t1hbm4OpVKJhQsX1v+kNBFHjx6Fo6MjRCIRNm7cCED/871+/XpIpVK0b98es2fPhr29PaRSKby8vHDy5ElNucDAQEgkEtjZ2Wm2ffDBB7CwsIBIJMK9e/cAAEFBQQgODkZGRgZEIpFm0q7vvvsOCoUCq1ataoxTwhhj7P9rMclITEwM3nrrLUycOBHZ2dm4desWFi9ejCtXrgAAli9fjtDQUISFhSE3NxdHjhxBVlYWhg0bhrt37wIA5s6di/nz56OsrAxWVlZISEhARkYGXFxcMHPmTKjVagDApUuX0KVLF3Tu3BmnTp2CXC4HAKxduxbvvfcePvvsM0yfPt2g+JcuXYpFixZh1qxZuHv3LnJychASEmK8EySwoUOH6twS0fd8BwYGYvr06VCpVJg3bx5u3LiBs2fPoqKiAq+++qpmrYX169dj8uTJWm3ExsZixYoVWttiYmIwduxYuLq6gohw/fp1AEBlZSWAx4N+GWOMNZ4WkYyo1WqsWLEC3t7eCAkJga2tLWxsbPDee+9h4MCBKCsrQ1RUFPz8/DBt2jQolUp4eHhg8+bNuHfvHrZs2aJTp5eXFxQKBdq1awd/f3+UlpYiMzMTAGBqaop58+YhMzMTe/fu1eyjUqmQnJyMd99916D4y8rKEB0djVdeeQULFiyAtbU1ZDIZbG1t63dimpFnne9qZmZmmitb7u7uiIuLQ3FxMeLj440Sg4+PD4qKirB06VKj1McYY0w/LSIZuXjxIgoLCzFmzBit7dVJQ3p6OkpKSjBgwACt1wcOHAiJRKJ1qb8mEokEADT/qQOPH71VKpWIiYnRbNu5cyd8fX2hUCgMiv/69etQqVQYNWqUQfu1VDWd75oMGDAAcrlc61YbY4yx5qdFJCNFRUUAAGtr6xpfLywsBABYWlrqvGZtbY3i4mKD27S0tMT777+P48eP49SpUwCATZs2ITAw0OC6bt26BQBo166dwfu2dubm5sjLyxM6DMYYY/XQIpKRjh07AoBmgOLTqpOIr03PAAAgAElEQVSUmpKOwsJCODg41KndwMBAiMViREdH48iRI+jcuTNcXV0NrkcqlQIAHj16VKc4Wiu1Wl2v948xxljT0CKSkS5dusDW1hbff/99ja/37t0blpaWOHPmjNb2kydPory8HP37969Tuw4ODpg8eTL27NmDpUuXIigoqE719O7dGyYmJvj555/rtH9rdfjwYRARBg0apNlmZmb23Ns7jDHGmpYWkYyYm5tj8eLFOHLkCAIDA3H79m1UVVWhuLgYly9fhlQqRXBwMPbu3YudO3eiqKgIaWlpmDNnDuzt7TFr1qw6tx0cHIyKigoUFBRg5MiRdaqjXbt2eP3117Fnzx5s374dRUVFuHjxYo0Da1uzqqoqFBQUoKKiAhcvXkRQUBAcHR21nlxyc3PD/fv3kZKSArVajby8PNy8eVOnLltbW2RnZ+PGjRsoLi6GWq3GwYMH+dFexhgTAjVBEydOpIkTJxq838aNG8nDw4OkUilJpVLq27cvxcbGEhFRVVUVRUZGUteuXUksFpONjQ1NmDCBrly5otk/NjaW5HI5AaCuXbtSRkYGbdmyhRQKBQEgJycnunr1qk673t7etG3bthpjSk1NpSFDhpC9vT0BIABkZ2dHXl5e9PPPP2vKFRcX04wZM6hNmzZkaWlJQ4cOpWXLlhEAcnBwoAsXLhh0LvRtVx91fT+etGHDBrKzsyMAJJfLady4cQad71mzZpFYLKZOnTqRmZkZKRQK8vX1pYyMDK128vPzydvbm6RSKTk7O9NHH31ECxcuJADk5uZGmZmZRER09uxZcnJyIplMRkOHDqWcnBw6cOAAWVlZUURERL2OlYgoISGBmujHizUzxvj8MUZEBIASEhKEDqMmiSKiJjBP+FMmTZoEAEhKShI4EgY0jfdj9uzZSEpKQn5+vmAxGCIxMRFTpkxpEtPws+atKXz+WMsgEomQkJCgMx9TE5DUIm7TsNahelIyxhhjLQsnI83Eb7/9BpFI9Nwff39/oUNljDHGDMLJSDPRo0cPENFzf3bv3i10qEa3ePFixMfH48GDB3B2dsaePXuEDqnB/fDDDwgNDUVycjJcXFw0yeabb76pU3b06NGwsrKCqakpevXqhbNnzwoQsWH++c9/YuDAgbCysoKTkxPeeecd5OTk1Fi2qqoK0dHR8PLyqleb4eHhcHd3h0KhgLm5Odzc3PDJJ5+gpKREq1xERESNiX7v3r116lSr1Vi9ejXc3NwgkUhgbW2N3r1748aNGwCAb775BmvWrBH0qh73pT9xX2rChBmr8mw8YKtp4ffDcPUZwLps2TIaO3YsFRUVaba5urpSmzZtCADt379fZ5+DBw/S+PHj6xxvY9q9ezcBoDVr1lBhYSGdO3eOXFxcyNPTk9RqtVbZq1ev0pAhQwgA9enTp17tDh8+nGJjYyk/P5+KioooISGBxGIx/eUvf9Eqt3LlSs2g7yd/evXqpVPnhAkTqHv37nTixAlSq9WUnZ1N48aNo7S0NE2ZmJgYGj58OBUUFNQp7vp8/rgv/Yn7UtMewMrJCHsufj8MV9dk5NNPP6Vu3bpRWVmZ1nZXV1f6+uuvycTEhDp16kSFhYVarzenLxBvb2/q2LEjVVVVabZt3LiRANDRo0c1286fP09+fn60c+dO8vT0rPcXiI+PD1VUVGhtmzx5MgHQPGVF9PgL5Kuvvnpufbt27SKRSEQXL158btnAwEAaPHiwzhekPur6+eO+xH3paU05GeHbNIw1EdevX8fSpUuxYsUKzay8T/Ly8kJQUBBu376Njz/+WIAIjSMrKwv29vYQiUSabZ07dwYArTlh+vTpg+TkZAQEBMDc3Lze7e7fvx+mpqZa29q2bQvg8SKXhtq0aRP69esHDw+P55Zdvnw5zp8/r7WWVUPivsR9qbnhZISxJmL9+vUgIowbN67WMhEREejWrRu2bduGH3744Zn1ERGioqI0Kx3b2NjA19dXa2HBuLg4WFhYQC6XY9++fXjttdegUCjg4OCAXbt2adVXWVmJZcuWwdHRETKZDC+88AISEhIMPk4XFxfk5uZqbau+x+/i4mJwffVx+/ZtyGQyODs7G7RfeXk5Tpw4AU9PT73K29jYYPjw4YiJiWmUx725L3Ffam44GWGsifj222/RvXt3yOXyWsvIZDLs2LEDJiYmmDlzJkpLS2stu3z5coSGhiIsLAy5ubk4cuQIsrKyMGzYMNy9excAMHfuXMyfPx9lZWWwsrJCQkICMjIy4OLigpkzZ2pNrR8SEoK1a9ciOjoad+7cwdixYzF16lSdZRaeZ/HixcjJycGGDRtQXFyM9PR0xMTEYMyYMVpT+zc0lUqFn376CTNnztSsFF0tNDQUNjY2kEgkcHZ2hq+vL06fPq15PTs7G+Xl5fj111/h7e0Ne3t7SKVS9OzZE7GxsTV+SfTt2xe3b9/GhQsXGvzYuC9xX2p2hLtFVDseo9C08PthOEPHjJSUlJBIJKKxY8fW+Lqrqyv98ccfmt+Dg4MJAH344YdEpHufX6VSkaWlJfn7+2vVc+rUKQJA4eHhmm1hYWEEQGtsQWxsLAGg69evExFRWVkZyeVyrfpUKhWZm5vT3Llz9T7OakuWLNEa0Ofg4EBZWVm1ln/ppZfqfZ//aWFhYdStWzetwZ1ERJmZmXT27FkqLi6mR48eUWpqKvXt25dkMhldunSJiIjS0tIIAL366qt07Ngxys/Pp8LCQgoJCSEAtHPnTp32vvjiCwJA//jHPwyK09DPH/cl7ku1AY8ZMdyePXv0mleDfxr+Z8+ePfx+GPgzZcoUg/p7bm4uiOiZ/8k+KSIiAt27d0dsbCyOHj2q83p6ejpKSkowYMAAre0DBw6ERCLByZMnn1l/9X931f/NXrlyBSqVSuuRRJlMBjs7O61L9foICwvDli1b8OOPP6KkpAS///47vLy8MHjwYGRlZRlUV13t3bsXiYmJOHToEKysrLRe69y5M/r27QtLS0tIJBIMGjQI8fHxKCsrQ2xsLABoxh306tULXl5esLW1hVKpxIoVK6BUKmtcV6r6va2+ktBQuC9xX2qOzIQOoDaDBg3C/PnzhQ6DAYiOjgYAfj8MkJqaatAAs4cPHwKA3oPrpFIp4uPjMXToULz77rtYs2aN1uuFhYUAAEtLS519ra2tUVxcrHdsADSX8JcsWYIlS5ZovWZvb693PXfu3MGaNWsQGhqqWVjS2dkZW7duhY2NDSIjI7F+/XqDYjPU7t27ERUVhcOHD6Njx4567ePh4QFTU1NcvXoVwJ/HfO/ePa1yEokETk5OyMjI0KlDJpMB+PO9bijcl7gvNUdNNhlxcHBoivPnt0rVa2Lw+2EYQ5KR6j8uhkxoNHjwYCxYsADr1q3DypUr4ejoqHnN2toaAGr8oigsLISDg4Pe7QCPV5YGHiemQUFBBu37pGvXrqGyslLnD7dCoYCtrS3S09PrXLc+NmzYgEOHDuGnn36q8cu1NlVVVaiqqtJ8wVtaWqJr1664fPmyTtmKigoolUqd7eXl5QD+fK8bCvcl7kvNUZO9TcNYa9K+fXuIRCI8ePDAoP1WrlyJHj164Ny5c1rbe/fuDUtLS50BgSdPnkR5eTn69+9vUDudO3eGVCrF+fPnDdrvadVfXHfu3NHaXlxcjPv372seyzQ2IsKiRYuQlpaGlJSUZ355jBkzRmfb6dOnQUQYPHiwZtuUKVNw7tw5/P7775ptKpUKN2/erPERzer3tkOHDvU5lOfivsR9qTniZISxJkAul8PFxQW3bt0yaL/qS+xPz3kglUoRHByMvXv3YufOnSgqKkJaWhrmzJkDe3t7zJo1y+B23nnnHezatQtxcXEoKipCZWUlbt26pfky8Pf3R4cOHZ45hbizszO8vb2xdetWHDlyBGVlZcjKytLE89577xkUl77tXr58GWvXrsXWrVshFot1xvisW7dOU/b27dvYvXs3CgsLoVarkZqaihkzZsDR0RFz5szRlFuwYAGcnJwwffp0ZGZmIj8/H4sWLUJZWRlCQkJ0Yqh+b/WZS6I+uC9xX2qWhBw+Wxt+eqNp4ffDcHWZgTUwMJDEYjGpVCrNtr1795KrqysBoLZt22qeeHjawoULdWbNrKqqosjISOratSuJxWKysbGhCRMm0JUrVzRlYmNjSS6XEwDq2rUrZWRk0JYtW0ihUBAAcnJyoqtXrxIR0aNHj2jRokXk6OhIZmZm1K5dO3r99dcpPT2diB5PZw2Ali1b9szjvHfvHgUFBZGbmxuZm5uTpaUlDRkyhP71r39plUtNTaUhQ4aQvb295kkJOzs78vLyop9//llTTp92q59YqO0nMjJSUzY4OJhcXV3JwsKCzMzMyMHBgWbOnEnZ2dk69WZlZdEbb7xBNjY2ZG5uTi+++CIdPHiwxhh8fHyoU6dOWrOF6qMunz/uS9yXaoIm/DQNJyPsufj9MFxdkpFr166RmZmZXtNHN0WVlZU0bNgw2r59e6to1xD37t0jqVRK69atM3jfunz+uC81r3YNUZ++1JSTEb5Nw1gT4ebmhvDwcISHh+us/tnUVVZWIiUlBcXFxfD392/x7Rpq+fLl8PT0RGBgYKO0x32p+bRrqMbuS42lVSQjV65cwUcffYRevXrBysoKZmZmUCqV6NatG3x8fJCamip0iBrPWuL66SXAq38kEgnat2+PESNGIDIyEgUFBQJEzowhNDQUkyZNgr+/v8EDEIV0+PBhJCcn4+DBg3rPb9Gc2zVEVFQUzp8/jwMHDkAsFjdau9yXmke7hhCqLzWGFp+MbN++HR4eHrh48SKioqKQlZWF0tJSnDt3DitXrkRhYSHS0tKEDhPA40fVXn75ZSxYsKDGxZZef/11/P7773B1dYVSqQQRoaqqCrm5uUhMTISzszMWLVqEXr16GTytMms6Vq1ahcDAQHz66adCh6K3UaNG4euvv4adnV2raFdf+/btw6NHj3D48GHY2Ng0evvcl5p+u/oSui81tCY7z4gxnDhxArNmzcLw4cNx6NAhmJn9ebguLi5wcXGBtbU1rl27JmCUj124cAHh4eGYM2cOSktL9V4ASSQSwdraGiNGjMCIESPg4+ODKVOmwMfHB1evXq3xGfXmqKysDKNGjcLx48ebdRv6Gj16NEaPHi10GKyexo8fj/HjxwsaA/ellqEp9KWG1KKvjERERKCyshKffvqpViLypDFjxuDDDz9s5Mh0GWuJ64kTJ2L69OnIzc3F5s2bjRihsLZv366zOmdzbIMxxpiuFpuMlJeX48cff0SbNm3w4osv6r0fGXGp7J49e0IkEsHExAT9+/fX3Hr55JNPoFQqIZVKsWPHDqMdc7Xp06cDAA4ePGj0uvWlz3kMDAyERCLRuiz6wQcfwMLCAiKRSDM9clBQEIKDg5GRkQGRSAQ3NzesX78eUqkU7du3x+zZszUrXXp5eWmtlVGfNgDgu+++g0KhwKpVqxr0fDHGWKsm7NM8NTPGo6RXr14lADRo0CCD9lu2bBlJJBL66quvqLCwkC5evEj9+vWjtm3bUk5OjqZc9eqUP/74Iz148IByc3Np2LBhZGFhQeXl5UREVFFRQV26dCFHR0eqqKjQamf+/PkUHR1dYwzPW1XS1dWVlEplra8XFRURAOrcubMhh16rurwf+p7HgIAA6tChg9a+kZGRBIDy8vI0215//XVydXXVKjdr1iyysLCgy5cv08OHDyk9PZ0GDhxIVlZWlJmZaZQ29u/fT1ZWVlork+qjLo/2MlYTfrSeGQv40d7GV1RUBKDmxZ1qU1ZWhqioKPj5+WHatGlQKpXw8PDA5s2bce/evRpXT/Ty8oJCoUC7du3g7++P0tJSZGZmAgBMTU0xb948ZGZmYu/evZp9VCoVkpOT8e6779bzKGtmZWUFkUhk8AJWxlKX81hXZmZmmqsv7u7uiIuLQ3FxMeLj441Sv4+PD4qKirB06VKj1McYY0xXi01GqpOQmp5KqY2xl8oGgBkzZkCpVGotmrZz5074+vpCoVDoHZshqgfANlT9z1Pf81gfAwYMgFwuN3gpcsYYY8JpsclIly5dIJVKNcs068PYS2VX1/X+++/j+PHjOHXqFABg06ZNDTphTfUx9+jRo8HaeJaGOI+GMDc3R15eXoO2wRhjzHhabDJibm6OMWPG4N69ezh27Fit5e7fv48ZM2YAMP5S2dUCAwMhFosRHR2NI0eOoHPnznB1da1TXfr47rvvAACvvfZag7XxLA11HvWhVqsbvA3GGGPG1WKTEeDxtLnm5uZYsGABysrKaixz6dIlzWO/xl4qu5qDgwMmT56MPXv2YOnSpQgKCqpTPfrIyclBdHQ0HBwcGmxMyvMYch7NzMy0bmvV1+HDh0FEGDRoUIO1wRhjzLhadDLi6emJr7/+GpcuXcKwYcNw4MABPHjwAGq1Gn/88Qe2bt2K9957TzOtrrGXyn5ScHAwKioqUFBQgJEjR9b72IgIJSUlqKqqAhEhLy8PCQkJGDJkCExNTZGSkiLYmBFDzqObmxvu37+PlJQUqNVq5OXl4ebNmzp12traIjs7Gzdu3EBxcbEmuaiqqkJBQQEqKipw8eJFBAUFwdHRUfN4c33bOHjwID/ayxhjDU3Yp3lqZuxH2TIzM+njjz8mDw8PsrS0JFNTU7K2tqa+ffvSe++9R8eOHdOUNfZS2U/y9vambdu21RijPktcf/PNN/TCCy+QXC4niURCJiYmBIBEIhFZW1vTiy++SOHh4ZSfn2+0c0dUt/dDn/NIRJSfn0/e3t4klUrJ2dmZPvroI1q4cCEBIDc3N80jumfPniUnJyeSyWQ0dOhQysnJoVmzZpFYLKZOnTqRmZkZKRQK8vX1pYyMDKO1ceDAAbKysqKIiAiDjp8f7WXGwo/2MmNBE360V0Sk57zjjWjSpEkAgKSkJIEjYUDTfT9mz56NpKQk5OfnCx2KjsTEREyZMkXvaf0Zq01T/fyx5kckEiEhIQGTJ08WOpSnJbXo2zSs5ausrBQ6BMYYY/XEyQhjjDHGBMXJCGuWFi9ejPj4eDx48ADOzs7Ys2eP0CExxhiro5qXsmWsiVu9ejVWr14tdBiMMcaMgK+MMMYYY0xQnIwwxhhjTFCcjDDGGGNMUJyMMMYYY0xQTXYA661bt5CYmCh0GAyP3wsA/H4YIDU1FQCfM1Z//PljrUGTnYGVH9VkjDHGjKupzsDaJJMRxljzwNPeM8aMgKeDZ4wxxpiwOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoDgZYYwxxpigOBlhjDHGmKA4GWGMMcaYoMyEDoAx1jzcunULb7/9NiorKzXbCgoKYGVlhREjRmiV7d69O/73f/+3kSNkjDVXnIwwxvTi4OCAmzdvIiMjQ+e1n3/+Wev3l19+ubHCYoy1AHybhjGmt7feegtisfi55fz9/RshGsZYS8HJCGNMbwEBAaioqHhmmV69esHd3b2RImKMtQScjDDG9Obq6ooXXngBIpGoxtfFYjHefvvtRo6KMdbccTLCGDPIW2+9BVNT0xpfq6iowKRJkxo5IsZYc8fJCGPMIG+88Qaqqqp0tpuYmGDQoEHo0qVL4wfFGGvWOBlhjBnE3t4eQ4YMgYmJ9p8PExMTvPXWWwJFxRhrzjgZYYwZ7M0339TZRkTw8/MTIBrGWHPHyQhjzGATJ07UGjdiamqKV155Be3btxcwKsZYc8XJCGPMYDY2Nnj11Vc1CQkRYdq0aQJHxRhrrjgZYYzVybRp0zQDWcViMXx9fQWOiDHWXHEywhirk3HjxsHc3BwAMHbsWFhaWgocEWOsueJkhDFWJxYWFpqrIXyLhjFWHyIioic3JCYmYsqUKULFwxhjjLEW7Km0AwCSal21NyEhoWGjYcwAU6ZMQVBQEAYPHix0KM1GdHQ0AGD+/PkN1kZlZSUSEhIwderUBmuDCY8/f8wYUlNTERMTU+NrtV4ZqSFzYUwwIpEICQkJmDx5stChNBvV07InJSU1aDsPHz6EVCpt0DaYsPjzx4zhGflFEo8ZYYzVCycijLH64mSEMcYYY4LiZIQxxhhjguJkhDHGGGOC4mSEMcYYY4LiZKQRrFu3Du3bt4dIJMLmzZs12w8cOAClUol///vfDR5DVVUVoqOj4eXlpVf5GTNmwMrKCiKRCOfPn2+0dhtaY55zxhhj+uFkpBF8/PHHOH78uM72xnp8+tq1a3j55ZexYMECqFQqvfbZtm0btm7d2ujtNjR+ZJ0xxpqeWic9Yw3Px8cHDx48aNA2Lly4gPDwcMyZMwelpaWN9mUsVLvP0xjnXF9lZWUYNWpUjYkqY4y1JnxlpAUhIiQlJWHLli2abX369EFycjICAgI0i5rpSyQS1TmW+rTbWmzfvh25ublCh8EYY4KrdzISExMDCwsLmJiYoH///ujQoQPEYjEsLCzQr18/DBs2DJ07d4ZUKoW1tTU++eQTrf1/+eUXuLu7Q6lUQiqVwsPDA4cOHQIA7NixA5aWlhCJRLCxsUFKSgrOnDkDJycnmJqaGjwF9fr16yGVStG+fXvMnj0b9vb2kEql8PLywsmTJ7XKEhGioqLQs2dPmJubw8bGBr6+vvjtt9/qVO5pR48ehaOjI0QiETZu3AgAiIuLg4WFBeRyOfbt24fXXnsNCoUCDg4O2LVrl9b+lZWVWL16Nbp37w6ZTIa2bdvC2dkZq1evrtMsiUSEyMhIdO/eHebm5lAqlVi4cKHB9TRl9Tnn+vadwMBASCQS2NnZabZ98MEHsLCwgEgkwr179wAAQUFBCA4ORkZGBkQiEdzc3AAA3333HRQKBVatWtUYp4QxxpoGekpCQgLVsPmZ/v73vxMAOnnyJJWWltK9e/foL3/5CwGgb7/9lvLy8qi0tJQCAwMJAJ0/f16zb1JSEi1fvpzu379P+fn5NGjQIGrTpo3m9cuXL5NcLqe3335bsy00NJS2bdtmUIzVZs2aRRYWFnT58mV6+PAhpaen08CBA8nKyooyMzM15ZYtW0YSiYS++uorKiwspIsXL1K/fv2obdu2lJOTY3C5a9euEQDatGmTZltWVhYBoA0bNmi2hYWFEQD68ccf6cGDB5Sbm0vDhg0jCwsLKi8v15RbtWoVmZqa0r59+0ilUtGvv/5KHTp0oBEjRtR67C+99BL16dOnxtfCwsJIJBLR559/TgUFBaRSqSg2NpYA0Llz5ww7yQa0qy8AlJCQUK86iOp3zvXtOwEBAdShQwetdiMjIwkA5eXlaba9/vrr5OrqqlVu//79ZGVlReHh4fU+1okTJ9LEiRPrXQ9jxvr8sdbtGflFolFv07i7u0Mul6NNmzZ44403AACOjo5o27Yt5HK5ZpnxJ68aTJw4EX//+99hY2MDW1tbjBs3Dvn5+cjLywMA9OzZE9HR0fjyyy/x9ddfY9euXXj06BHee++9OsdpZmamuZLh7u6OuLg4FBcXIz4+HsDje/lRUVHw8/PDtGnToFQq4eHhgc2bN+PevXua2yD6lqsLLy8vKBQKtGvXDv7+/igtLUVmZqbm9ZSUFPTv3x/jxo2DTCZDv379MH78eBw5cgTl5eUGtVVWVobo6Gi88sorWLBgAaytrSGTyWBra1vn+Juj551z4Pl9p758fHxQVFSEpUuXGqU+xhhrDhpsAKtEIgEAVFRUaLaJxWIAgFqtrnW/6jKVlZWabe+//z7+85//YPbs2XjllVewZ88eo8Y6YMAAyOVyTZKUnp6OkpISDBgwQKvcwIEDIZFINJfl9S1XX9Xn8snzVtPiZJWVlRCLxTA1NTWo/uvXr0OlUmHUqFH1D7aFqOmc1+TpvsMYY8xwgg9g/fbbbzFixAi0a9cO5ubmOmNKqq1atQolJSUNNuDP3NxcczWmsLAQAGBpaalTztraGsXFxQaVawh//etf8euvv2Lfvn0oKyvDmTNnkJKSgr/97W8GJyO3bt0CALRr164hQm3xnuw7jDHGDCdoMpKZmYkJEybAzs4OJ0+exIMHD7BmzRqdcmq1GvPmzUNUVBRSU1MRERFh1DjUajUKCwvh4OAA4HEiAaDGZKIu5RrC8uXLMXLkSEyfPh0KhQJ+fn6YPHlyneYGqb7C8ujRI2OH2eI93XcYY4wZTtB5RtLS0qBWqzF37ly4uLgAqPlx0o8++ggzZ86En58fbt++jZUrV2L06NEYPHiwUeI4fPgwiAiDBg0CAPTu3RuWlpY4c+aMVrmTJ0+ivLwc/fv3N6hcQ0hPT0dGRgby8vJgZla/t7F3794wMTHBzz//jDlz5hgpwtbh6b4DPB5X8rzbO4wxxv4k6JURR0dHAMAPP/yAhw8f4tq1azrjLGJjY9GpUyf4+fkBAFavXg13d3cEBASgqKioTu1WVVWhoKAAFRUVuHjxIoKCguDo6Ijp06cDeHylIDg4GHv37sXOnTtRVFSEtLQ0zJkzB/b29pg1a5ZB5RrChx9+CEdHR5SUlNS7rnbt2uH111/Hnj17sH37dhQVFeHixYv1GoDbUj2v7wCAm5sb7t+/j5SUFKjVauTl5eHmzZs6ddna2iI7Oxs3btxAcXEx1Go1Dh48yI/2MsZaHwMevalRTEwMyeVyAkBdunShX375hT777DNSKpUEgDp06EBff/017d69mzp06EAAyMbGhnbt2kVERLDWn48AACAASURBVIsWLSJbW1uytramSZMm0caNGwkAubq6kqenJ4lEIrK1taXjx48TEdH8+fPJxMSEAJBSqaQzZ84Y9GjRrFmzSCwWU6dOncjMzIwUCgX5+vpSRkaGVrmqqiqKjIykrl27klgsJhsbG5owYQJduXLF4HKff/655tgtLCzIz8+PNmzYQHZ2dgSA5HI5jRs3jmJjYzXnsmvXrpSRkUFbtmwhhUJBAMjJyYmuXr1KREQ//fQTtWnThgBofsRiMfXs2ZOSk5M1baemptKQIUPI3t5eU87Ozo68vLzo559/1pQrLi6mGTNmUJs2bcjS0pKGDh1Ky5YtIwDk4OBAFy5cMOg869uuvmCERwvre8717Tv5+fnk7e1NUqmUnJ2d6aOPPqKFCxcSAHJzc9M8Bnz27FlycnIimUxGQ4cOpZycHDpw4ABZWVlRREREvY6ViB/tZcZjjM8fY896tFdEpD1Pd2JiIqZMmdJkpu82ttmzZyMpKQn5+flCh1IvcXFxuHbtGqKjozXbysvLERISgri4OBQUFEAmkwkYoXGJRCIkJCTUaUI3Y2lufWfSpEkAgKSkJIEjYc1dU/j8sebvGflFUqtcm+bJx4abo5ycHAQGBuqspiuRSODo6Ai1Wg21Wt2ikpGmorn3HcYYa4oEf7S3vn777TeIRKLn/vj7+wsdqtHIZDKIxWJs374dd+/ehVqtRnZ2NrZt24Zly5bB398fCoXCqG22xvPc2v3www8IDQ1FcnIyXFxcNO/xm2++qVN29OjRsLKygqmpKXr16oWzZ88KELFh/vnPf2LgwIGwsrKCk5MT3nnnHeTk5NRYtqqqCtHR0fDy8qpXm+Hh4XB3d4dCoYC5uTnc3NzwySef6Iz9ioiIqPHz1bt3b5061Wo1Vq9eDTc3N0gkElhbW6N37964ceMGAOCbb77BmjVrBEukW3o/etLDhw/Ro0cPLFmypMbXuR89gwH3dJq90NBQkkgkmvEtSUlJQodUZ0eOHKFXXnmFFAoFmZqaklKpJC8vL4qNjSW1Wi10eEYHge9ZN8e+U58xI8uWLaOxY8dSUVGRZpurq6tmnNL+/ft19jl48CCNHz++zvE2pt27dxMAWrNmDRUWFtK5c+fIxcWFPD09dT4/V69epSFDhhCAei9rMHz4cIqNjaX8/HwqKiqihIQEEovF9Je//EWr3MqVK7XGg1X/9OrVS6fOCRMmUPfu3enEiROkVqspOzubxo0bR2lpaZoyMTExNHz4cCooKKhT3HX9/LX0fvS0BQsWEAAKCwvTeY370bPHjLSqZIQ1X0InI81RXZORTz/9lLp160ZlZWVa211dXenrr78mExMT6tSpExUWFmq93py+RLy9valjx45UVVWl2VY9eP7o0aOabefPnyc/Pz/auXMneXp61vtLxMfHhyoqKrS2TZ48mQBorW+0cuVK+uqrr55b365du0gkEtHFixefWzYwMJAGDx5cp39W6vL5aw396EnHjh2j0aNH15iMcD96rNHWpmGMNW/Xr1/H0qVLsWLFCp3lBoDH6/cEBQXh9u3b+PjjjwWI0DiysrJgb2+vNa9R586dAUDrMew+ffogOTkZAQEBMDc3r3e7+/fv15khuW3btgAAlUplcH2bNm1Cv3794OHh8dyyy5cvx/nz5xETE2NwO4ZqLf2oWllZGRYuXFjrueV+9HycjDDGNNavXw8iwrhx42otExERgW7dumHbtm344YcfnlkfESEqKkqzuKCNjQ18fX211vKJi4uDhYUF5HI59u3bh9deew0KhQIODg7YtWuXVn2VlZVYtmwZHB0dIZPJ8MILLyAhIcHg43RxcdFZWqJ6vEj1BIyN5fbt25DJZHB2djZov/Lycpw4cQKenp56lbexscHw4cMRExPT4E9LtpZ+VC0sLAwffPCBoEtqNPd+xMkIY0zj22+/Rffu3SGXy2stI5PJsGPHDpiYmGDmzJkoLS2ttezy5csRGhqKsLAw5Obm4siRI8jKysKwYcNw9+5dAMDcuXMxf/58lJWVwcrKCgkJCcjIyICLiwtmzpypNZttSEgI1q5di+joaNy5cwdjx47F1KlTdWZBfp7FixcjJycHGzZsQHFxMdLT0xETE4MxY8Zozabb0FQqFX766SfMnDlTszhjtdDQUNjY2EAikcDZ2Rm+vr44ffq05vXs7GyUl5fj119/hbe3N+zt7SGVStGzZ0/ExsbW+EXRt29f3L59GxcuXGjQ42ot/QgAjh07hoyMDEydOtXgfY2lRfQjA+7pMCYY8JgRgxk6ZqSkpIREIhGNHTu2xtddXV3pjz/+0PweHBxMAOjDDz8kIt17/SqViiwtLcnf31+rnlOnThEACg8P12wLCwsjAFrjC2JjYwkAXb9+nYiIysrKSC6Xa9WnUqnI3Nyc5s6dq/dxVluyZInWoD4HBwfKysqqtfxLL71U73v9TwsLC6Nu3bppDfAkIsrMzKSzZ89ScXExPXr0iFJTU6lv374kk8no0qVLRESUlpZGAOjVV1+lY8eOUX5+PhUWFlJISAgBoJ07d+q098UXXxAA+sc//mFQnIZ8/lpTP1KpVDRgwAC6desWERHl5eXVOoC1WmvuR88aM1LrPCOJiYnGy3gYM4LU1FShQ2hWbt26ZdACfrm5uSCiZ/43+6SIiAjs378fsbGxmDJlis7r6enpKCkpwYABA7S2Dxw4EBKJRGfph6dV/4dX/R/tlStXoFKptB5LlMlksLOz07pcr4+wsDBs27YNP/74I1566SXk5uYiJCQEgwcPxvHjxzXjRxrS3r17kZiYiO+//x5WVlZar3Xu3FkrhkGDBiE+Ph6enp6IjY1FXFycZuxBr169tB4VXbFiBTZt2oQtW7YgICBAq97q97b6akJDaE39aPHixXj//ffRqVMng/YzppbSj2pNRmrqFIwJKSYmplEG37UkEydO1Lvsw4cPAUDvAXZSqRTx8fEYOnQo3n33XZ0VtwsLCwEAlpaWOvtaW1vXuNr1s1Rfxl+yZInOPA729vZ613Pnzh2sWbMGoaGhGDlyJADA2dkZW7duhY2NDSIjI7F+/XqDYjPU7t27ERUVhcOHD6Njx4567ePh4QFTU1NcvXoVwJ/HfO/ePa1yEokETk5OyMjI0KmjeiLE6ve6IbSWfnT06FGkpf0/9u49Lqpq/R/4Z4CB4TYDCAKKIBdvpGleSlBTtKOZaYp3sZOmhpQhSoqXNEMhFQ9wVMiv6KFe2VFAONgxrb7pIctbWV4IvylRCl6Qi9xBGeD5/eFv9nGcQWdgYAM+79dr/nDN2ns9s/ca52HvtdfKRHR0tF7tG1JH6keNjhkhIn7xq828ACApKUn0ONrTS59EBPjvfzD6TGrk4+OD5cuXIzs7Gxs3blR7z8bGBgC0/liUlpbqddUGgDA4MCYmRuOz6nPVLDs7G/X19Rr/ecvlctjZ2SErK0uvuPS1Y8cO7Nu3D8ePH9f5BwR4MGFWQ0OD8CNvZWWFHj164PLlyxp16+rqoFAoNMpra2sBoEVnZ35a+tHevXtx7NgxGBkZCZOJqfYdEREBiUTSpDEouupo/YgHsDLGAACdO3eGRCJBWVmZXttt3LgRvXv3xvnz59XK+/btCysrK43/kM+ePYva2loMGjRIr3a6desGmUymsQyCvlQ/Xrdv31Yrr6iowN27d1vsFg0RISwsDJmZmUhPT9f6l77KuHHjNMp++uknEBF8fHyEspkzZ+L8+fP4448/hLLq6mpcv35d62OaqnPr6OjYnI/yWE9LP0pMTNRIZgoLCwE8uA1IRBq3lgyho/YjTkYYYwAe3Af28PDAjRs39NpOdZn90XkPZDIZQkNDkZaWhn379qG8vByZmZkICgqCs7MzAgMD9W5n/vz52L9/P+Lj41FeXo76+nrcuHFDSCxmzZoFR0fHx04j7u7uDj8/PyQkJODEiROoqalBXl6eEM+CBQv0ikvXdi9fvoytW7ciISEBUqlUY4rubdu2CXVv3ryJAwcOoLS0FEqlEqdPn8bChQvh6uqKoKAgod7y5cvh5uaGefPmITc3F8XFxQgLC0NNTQ1WrVqlEYPq3Ooyn0RTPS39qCU81f2IHsFP07C2CPw0jd6aMgNrcHAwSaVSqq6uFsrS0tLI09OTAJC9vb3w1MOjVqxYoTFzZkNDA0VFRVGPHj1IKpWSra0tTZkyha5cuSLUiYuLIwsLCwJAPXr0oJycHNq9ezfJ5XICQG5ubnT16lUiIrp//z6FhYWRq6srmZiYkIODA02dOpWysrKI6MGU1gBo/fr1j/2cRUVFFBISQl5eXmRmZkZWVlY0bNgw+te//qVW7/Tp0zRs2DBydnYWnrpxcnIiX19f+u6774R6urSremqhsVdUVJRQNzQ0lDw9PcnS0pJMTEzIxcWFFi1aRLdu3dLYb15eHs2ePZtsbW3JzMyMnn/+eTp69KjWGCZMmEBdu3ZVm3lWF/p+/56WfvSoxp6m4X70AE8Hz9o9Tkb015RkJDs7m0xMTHSaQrotqq+vpxEjRtDevXufinb1UVRURDKZjLZt26b3tvp+/7gfta929dGcfsTTwTPGdOLl5YXw8HCEh4drrADa1tXX1yM9PR0VFRWtunq0WO3qa8OGDRgwYACCg4NbvC3uR+2nXX21VD/iZIQxpmb16tWYPn06Zs2apfcgRDFlZGQgNTUVR48e1XmOi/bcrj6io6Nx4cIFHDlyBFKptFXa5H7UPtrVR0v2o1ZNRlJTU+Hh4SEMtFm3bt1j60dHR0MikcDIyAi9e/fGiRMnWiwWiUQCqVSKrl27IiAgAP/3f/9nsLYetW3bNmHE+a5du4TyI0eOQKFQ4N///neLta3S0NCAmJgYtUluVLQdG4lEAlNTU3Tu3BmjRo1CVFQUSkpKWjxOJo6IiAgEBwfjo48+EjsUnY0ZMwaff/45nJycnop2dXXo0CHcv38fGRkZsLW1bdW2uR+1/XZ11eL9SI97OgajGsTk5OREtbW1WuvU1dWRm5sbAaAxY8a0aCwKhYKIHkxj/MUXX5CrqytZWVnRb7/91mLtZmdnEwD6+OOPhbLDhw+TXC6nL774osXaJSK6evUqDRs2jAA8dlrih49NQ0MDlZSU0H/+8x+aN28eSSQScnZ2pp9++qlFY1UBjxnRW1PGjDCmDX//mCG0yTEjgwYNQn5+PtLT07W+n5qa2upT7FpaWmLixIn4+9//jsrKSuzYsaNV258wYQLKysowceLEFmvj4sWLWLVqFYKCgnRepREAJBIJbGxsMGrUKCQmJiI5ORl37twRYu7oampqtF5Fam9tMMZYWyRaMvL2228DAD7++GOt70dHRyM0NLQ1QxI8//zzAIBff/1VlPYNhYiQkpKC3bt3C2X9+/dHamoqAgICdJ6uWZtp06Zh3rx5KCgoULvV1FHt3btXY8n59tgGY4y1RaIlI6NHj0afPn3wn//8B1euXFF77+TJk6iursbYsWO1bvv999/D29sbCoUCMpkM/fr1w9dffw0A+OSTT2BlZQWJRAJbW1ukp6fj3LlzcHNzg7GxsU7LPNfV1QFQX1uBiBAdHY0+ffrAzMwMtra2mDx5ssbCSrrWe9QPP/wAV1dXSCQS7Ny5EwAQHx8PS0tLWFhY4NChQxg/fjzkcjlcXFywf/9+te3r6+sRGRmJXr16wdzcHPb29nB3d0dkZCRmzJjxxM/cFPPmzQMAHD16tEX23xy6nIfg4GCYmpqq3aN95513YGlpCYlEIqzVEBISgtDQUOTk5EAikcDLywvbt2+HTCZD586dsXjxYmHZbV9fX7WFu5rTBgB89dVXkMvliIiIaNHjxRhjotLjno7BqJaQ/vvf/04AKCQkRO39KVOmUGJiIlVUVGgdM5KSkkIbNmygu3fvUnFxMQ0dOpQ6deokvH/58mWysLCgN954QyhbvXo17dmzR2ssqnERKp999hkBoBUrVghl69evJ1NTU/rss8+otLSULl26RAMHDiR7e3vKz8/Xu562MSN5eXkEgHbs2CGUqZbEPnbsGJWVlVFBQQGNGDGCLC0t1cbbREREkLGxMR06dIiqq6vp559/JkdHRxo1alSj5+FJS1lrOzYPKy8vJwDUrVu3RusYCvS8Z63reQgICCBHR0e1baOioggAFRYWCmVTp04lT09PtXqBgYFkaWlJly9fpnv37lFWVhYNGTKErK2tKTc31yBtHD58mKytrdWWSdcVjxlhhqLv948xbdrkmBEAeOONN2BpaYlPP/0UNTU1AIA//vgDP/3002OvYEybNg0ffPABbG1tYWdnh0mTJqG4uFhYF6BPnz6IiYnBp59+is8//xz79+/H/fv3nzjNc1VVFVJTU/Hee++hc+fOWLp0KYAH9/Kjo6Ph7++PuXPnQqFQoF+/fti1axeKioqE2yC61msKX19fyOVyODg4YNasWaiqqkJubq7wfnp6OgYNGoRJkybB3NwcAwcOxGuvvYYTJ04IixoZmrW1NSQSid6rZra0ljwPjzIxMRGuvnh7eyM+Ph4VFRVITEw0yP4nTJiA8vLyJz55xhhj7ZmoyYhCocCcOXNQUlKCAwcOAHiwkuLbb78NU1NTnfejet754VUi33rrLUybNg2LFy9GcnIytm7d2uj2ZWVlkEgkUCgUWLp0KV555RX8+OOPwgDarKwsVFZWaix6NGTIEJiamgqX5XWt11yqY6NUKoWye/fuCavbqtTX10MqlWqs9WAoVVVVICLI5fIW2X9TtdZ50Gbw4MGwsLB44m05xhhj/yX6pGeqgay7du1CaWkpUlJSsHjx4sdu8+WXX2LUqFFwcHCAmZkZVq5cqbVeREQEKisrnzgoUKFQgIhQV1eHGzdu4B//+Afc3NyE90tLSwFA6+qINjY2wpUBXeu1hFdeeQU///wzDh06hJqaGpw7dw7p6el49dVXWywZuXr1KgCgd+/eLbL/phLzPAAPxhqprtIxxhh7MtGTkQEDBmDo0KH48ccfERgYiOnTpz92QpXc3FxMmTIFTk5OOHv2LMrKyrBlyxaNekqlEkuXLkV0dDROnz6NTZs2NTlGGxsbAND6I1ZaWiosSa5rvZawYcMGjB49GvPmzYNcLoe/vz9mzJiBhISEFmvzq6++AgCMHz++xdpoCjHPg1KpbPE2GGOsozEROwDgwdWRM2fO4ODBg8jOzn5s3czMTCiVSrz99tvw8PAA8GAOjEe9++67WLRoEfz9/XHz5k1s3LgRY8eOhY+Pj97x9e3bF1ZWVjh37pxa+dmzZ1FbW4tBgwbpVa8lZGVlIScnB4WFhTAxafnTmp+fj5iYGLi4uODNN99s8fb0oc95MDExUbvd1VwZGRkgIgwdOrTF2mCMsY5G9CsjADBjxgzY29tjypQpQoLRGFdXVwDAt99+i3v37iE7O1tjDEBcXBy6du0Kf39/AEBkZCS8vb0REBCA8vJyveOTyWQIDQ1FWloa9u3bh/LycmRmZiIoKAjOzs4IDAzUq15LWLJkCVxdXQ2+KBURobKyEg0NDSAiFBYWIikpCcOGDYOxsTHS09Pb3JgRfc6Dl5cX7t69i/T0dCiVShQWFuL69esa+7Szs8OtW7dw7do1VFRUCMlFQ0MDSkpKUFdXh0uXLiEkJASurq7CY8/NbePo0aP8aC9jrOPT49GbZktLSxOmgre3t6clS5YI761cuZJOnTol/Pv9998nJycnAkBGRkbk7e1N33//PRERhYWFkZ2dHdnY2ND06dNp586dBIA8PT1pwIABJJFIyM7OTtjfsmXLyMjIiACQQqGgc+fO0cmTJ6lnz54EgACQs7MzTZ8+vdHYGxoaKCoqinr06EFSqZRsbW1pypQpdOXKFb3r/e1vfyNHR0cCQJaWluTv7087duwQPq+FhQVNmjSJ4uLiyMLCggBQjx49KCcnh3bv3k1yuZwAkJubG129epWIiI4fP06dOnUSPg8Akkql1KdPH0pNTRXaPn36NA0bNoycnZ2Fek5OTuTr60vfffcdERF98cUX9Oyzz5KFhQWZmpoKx04ikZCNjQ09//zzFB4eTsXFxU3tCnqDno8W6nq+iouLyc/Pj2QyGbm7u9O7775LK1asIADk5eUlPKL7yy+/kJubG5mbm9Pw4cMpPz+fAgMDSSqVUteuXcnExITkcjlNnjyZcnJyDNbGkSNHyNramjZt2qT3MeNHe5mh6Pv9Y0ybxz3aKyFSfwQjOTkZM2fO1Hgyg7Vt8fHxyM7ORkxMjFBWW1uLVatWIT4+HiUlJTA3NxcxwuaRSCRISkpqsQncmmLx4sVISUlBcXGx2KFoNX36dABASkqKyJGw9q4tfv9Y+/OY/CKlTYwZYc2Tn5+P4OBgXLhwQa3c1NQUrq6uUCqVUCqV7ToZaasefpycMcZY07SJMSOseczNzSGVSrF3717cuXMHSqUSt27dwp49e7B+/XrMmjWrzY3rYIwxxlQ4GekAFAoFvvnmG/z666/o2bMnzM3N4e3tjcTERGzevBmffvqp2CF2OGvWrEFiYiLKysrg7u6OgwcPih0SY4y1W3ybpoMYMWIE/vd//1fsMJ4akZGRiIyMFDsMxhjrEPjKCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZE1egAVtWESYy1FTExMTyBlx7OnDkDgL/LzDD4+8ea68aNG42+pzED6+nTpxEdHd3iQTHG2r/8/HycP3++za3czBhru7QktSkayQhjjOmKl49gjBlACo8ZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlhjDHGmKhMxA6AMdY+KJVKVFZWqpVVVVUBAEpKStTKJRIJbGxsWi02xlj7xskIY0wnd+/eRdeuXVFfX6/xnp2dndq//fz8cPz48dYKjTHWzvFtGsaYThwdHfHiiy/CyOjx/21IJBLMnj27laJijHUEnIwwxnT2+uuvP7GOsbEx/P39WyEaxlhHwckIY0xnU6dOhYlJ43d3jY2N8fLLL6NTp06tGBVjrL3jZIQxpjO5XI7x48c3mpAQEebOndvKUTHG2jtORhhjepk7d67WQawAYGpqildffbWVI2KMtXecjDDG9PLqq6/CwsJCo1wqlWLKlCmwtLQUISrGWHvGyQhjTC8ymQz+/v6QSqVq5UqlEgEBASJFxRhrzzgZYYzpbc6cOVAqlWplcrkcf/nLX0SKiDHWnnEywhjT20svvaQ20ZlUKsXs2bNhamoqYlSMsfaKkxHGmN5MTEwwe/Zs4VaNUqnEnDlzRI6KMdZecTLCGGuS2bNnC7dqHB0dMXz4cJEjYoy1V5yMMMaaxNfXF127dgUA/PWvf33iNPGMMdaYNrlQ3unTp5GXlyd2GIyxJxgyZAhu3ryJTp06ITk5WexwGGNP4OvrCxcXF7HD0CAhIhI7iEdNnz4dBw8eFDsMxhhjrENJSkrCjBkzxA7jUSlt8soIAEybNg0pKSlih8HwIDkEwOdDD8nJyZg5cybaYK5vcAcPHsS0adPEDqPD4u8fMxSJRCJ2CI3im7yMsWbhRIQx1lycjDDGGGNMVJyMMMYYY0xUnIwwxhhjTFScjDDGGGNMVJyMMMYYY0xUnIy0koaGBsTExMDX11en+gsXLoS1tTUkEgkuXLigd3vh4eHw9vaGXC6HmZkZvLy8sHLlSlRWVuq9L0M5cuQIFAoF/v3vf4sWA2OMsbaHk5FWkJ2djRdffBHLly9HdXW1Ttvs2bMHCQkJTW7z+PHjWLJkCa5du4aioiJERkYiNjZWmLNADE/DnBuMMcb012YnPesoLl68iPDwcAQFBaGqqqrVfpCtrKwQGBgIY2NjAMCMGTOQmpqK5ORk5OXloVu3bq0Sx8MmTJiAsrKyVm9Xm5qaGowZMwanTp0SOxTGGHvq8ZWRFta/f3+kpqYiICAAZmZmem3bnNnyDh8+LCQiKvb29gCg89WZjmzv3r0oKCgQOwzGGGPoYMnIZ599hsGDB0Mmk8HS0hLdu3fHxo0bATy4RRAdHY0+ffrAzMwMtra2mDx5Mn777Tdh+/j4eFhaWsLCwgKHDh3C+PHjIZfL4eLigv379wv1+vTpA4lEAiMjIwwaNEj4cV+5ciUUCgVkMhk++eQTvWInIkRFRaFXr14wMzODQqHAihUrmn9QHnLz5k2Ym5vD3d3doPvVxQ8//ABXV1dIJBLs3LkTgO7He/v27ZDJZOjcuTMWL14MZ2dnyGQy+Pr64uzZs0K94OBgmJqawsnJSSh75513YGlpCYlEgqKiIgBASEgIQkNDkZOTA4lEAi8vLwDAV199BblcjoiIiNY4JIwxxv6/DpOMxMbG4q9//SumTZuGW7du4caNG1izZg2uXLkCANiwYQNWr16NtWvXoqCgACdOnEBeXh5GjBiBO3fuAADefvttLFu2DDU1NbC2tkZSUhJycnLg4eGBRYsWQalUAgB+/fVXdO/eHd26dcOPP/4ICwsLAMDWrVuxYMECbN68GfPmzdMr/nXr1iEsLAyBgYG4c+cO8vPzsWrVKoMdn+rqahw/fhyLFi2Cqampwfarq+HDh2vcEtH1eAcHB2PevHmorq7G0qVLce3aNfzyyy+oq6vDX/7yF2GF5+3bt2ssABUXF4cPP/xQrSw2NhYTJ06Ep6cniAi///47AKC+UCrTMQAAIABJREFUvh7Ag8HGjDHGWk+HSEaUSiU+/PBD+Pn5YdWqVbCzs4OtrS0WLFiAIUOGoKamBtHR0fD398fcuXOhUCjQr18/7Nq1C0VFRdi9e7fGPn19fSGXy+Hg4IBZs2ahqqoKubm5AABjY2MsXboUubm5SEtLE7aprq5Gamoq3nzzTb3ir6mpQUxMDF566SUsX74cNjY2MDc3h52dXfMOzEMiIyPh7OyMTZs2GWyfhvS4461iYmIiXNny9vZGfHw8KioqkJiYaJAYJkyYgPLycqxbt84g+2OMMaabDpGMXLp0CaWlpRg3bpxauSppyMrKQmVlJQYPHqz2/pAhQ2Bqaqp2qV8b1ZUE1V/qwINHbxUKBWJjY4Wyffv2YfLkyZDL5XrF//vvv6O6uhpjxozRaztdpaWlITk5GV9//TWsra1bpA1D0na8tRk8eDAsLCzUbrUxxhhrfzpEMlJeXg4AsLGx0fp+aWkpgAdPmDzKxsYGFRUVerdpZWWFt956C6dOncKPP/4IAPj4448RHBys975u3LgBAHBwcNB72yc5cOAANm/ejIyMDHTv3t3g+xebmZkZCgsLxQ6DMcZYM3SIZKRLly4AIAxQfJQqSdGWdJSWlsLFxaVJ7QYHB0MqlSImJgYnTpxAt27d4Onpqfd+ZDIZAOD+/ftNiqMxO3bswL59+3D8+HHhGHUkSqWyWeePMcZY29AhkpHu3bvDzs4O33zzjdb3+/btCysrK5w7d06t/OzZs6itrcWgQYOa1K6LiwtmzJiBgwcPYt26dQgJCWnSfvr27QsjIyN89913Tdr+UUSEsLAwZGZmIj09XesVoY4gIyMDRIShQ4cKZSYmJk+8vcMYY6xt6RDJiJmZGdasWYMTJ04gODgYN2/eRENDAyoqKnD58mXIZDKEhoYiLS0N+/btQ3l5OTIzMxEUFARnZ2cEBgY2ue3Q0FDU1dWhpKQEo0ePbtI+HBwcMHXqVBw8eBB79+5FeXk5Ll26pHVgrS4uX76MrVu3IiEhAVKpFBKJRO21bdu2Ju1XbA0NDSgpKUFdXR0uXbqEkJAQuLq6qj255OXlhbt37yI9PR1KpRKFhYW4fv26xr7s7Oxw69YtXLt2DRUVFVAqlTh69Cg/2ssYYyLoEMkI8CAp2LlzJzIyMuDl5QVLS0uMHDkSGRkZAIAPPvgAkZGRCA8Ph729PUaOHInu3bsjIyMDlpaWAB7MexETEwMAePbZZ/HHH38gISEBoaGhAICXX34Z2dnZau0+99xz8PPzw9KlS7XGdebMGQwfPhxdunTB2bNncfHiRTg7O2PYsGE4ceKEUO8f//gH5s+fj7CwMHTt2hXvvPMORowYAQCYOHEiLl26pPOxaIvTru/cuRNDhgwBAISFheG1117T+3jfu3cP/fr1g7m5OUaMGIGePXviP//5j9pkcm+//Tb8/Pwwe/Zs9OrVCxs3boS5uTkAwMfHR3gMOCgoCJ07d4a3tzdeeeUV3L17t1WOA2OMMU0SaoO/XKr1U1JSUkSOhAFt43wsXrwYKSkpKC4uFi0GfSQnJ2PmzJltMjFk7Utb+P6xjkEikSApKUljPqY2IKXDXBlhHZ9qUjLGGGMdCycj7cRvv/2mMfZD22vWrFlih8oM4Ntvv8Xq1auRmpoKDw8P4fy+/vrrGnXHjh0La2trGBsb45lnnsEvv/wiQsRNd+/ePfTu3Rvvv/++1vcbGhoQExMDX1/fZrUTHh4Ob29vyOVymJmZwcvLCytXrkRlZaVavU2bNmn9bvXt21djn0qlEpGRkfDy8oKpqSlsbGzQt29fXLt2DQDwxRdfYMuWLaIm0tyX/stQfUnX/ena5wDgn//8J4YMGQJra2u4ublh/vz5yM/PF95vC32pRVEbNG3aNJo2bZrYYbD/T+zzsXr1ajI1NSUA1L17d0pJSREtFl0lJSVRU79e69evp4kTJ1J5eblQ5unpSZ06dSIAdPjwYY1tjh49Sq+99lqT4xXT8uXLCQCtXbtW472rV6/SsGHDCAD179+/We2MHDmS4uLiqLi4mMrLyykpKYmkUim9/PLLavU2btxIADRezzzzjMY+p0yZQr169aIzZ86QUqmkW7du0aRJkygzM1OoExsbSyNHjqSSkpImxd2c7x/3pf8yZF/SdX+69rkDBw4QANqyZQuVlpbS+fPnycPDgwYMGEBKpVKo19y+BICSkpKatG0LS+YrI6zNi4yMxP3790FE+PPPPzFt2jSxQ2oxmzdvxoEDB5CcnKwxW+727dthZGSEwMBAlJWViRShYZ06dQq//vqr1vcuXryIVatWISgoCAMGDGh2W1ZWVggMDISdnR2sra0xY8YMTJkyBV999ZUwsFnls88+AxGpvR6N88CBA0hPT0dKSgpeeOEFmJiYwNnZGYcOHVK7irJ06VL0798fr7zyCurq6pr9OXTFfem/DN2XdN2frn3uf/7nf9ClSxesWLECCoUCAwYMwPLly3HhwgW1GcLF6kutgZMRxtqI33//HevWrcOHH34oTIT3MF9fX4SEhODmzZt47733RIjQsGpqarBixQq1JRUe1r9/f6SmpiIgIEDtiammOnz4MIyNjdXK7O3tAUBYeVsfH3/8MQYOHIh+/fo9se6GDRtw4cKFRj+roXFfUmfovqTr/nTtc3l5eXB2doZEIhHKunXrBgAaUxO0dl9qLZyMMNZGbN++HUSESZMmNVpn06ZN6NmzJ/bs2YNvv/32sfsjIkRHRwuLC9ra2mLy5Mlqa/nEx8fD0tISFhYWOHToEMaPHw+5XA4XFxfs379fbX/19fVYv349XF1dYW5ujmeffRZJSUlN/rxr167FO++80yLLIOjq5s2bMDc3h7u7u17b1dbW4syZMzr/lW1ra4uRI0ciNja2VZ6w4r7Udmnrcx4eHigoKFCrpxov4uHhoVbe2n2ptXAywlgb8eWXX6JXr16wsLBotI65uTk++eQTGBkZYdGiRaiqqmq07oYNG7B69WqsXbsWBQUFOHHiBPLy8jBixAjcuXMHwIN5WZYtW4aamhpYW1sjKSkJOTk58PDwwKJFi9Rms121ahW2bt2KmJgY3L59GxMnTsScOXM0ZjbWxcmTJ5GTk4M5c+bova2hVFdX4/jx41i0aJGwOKPK6tWrYWtrC1NTU7i7u2Py5Mn46aefhPdv3bqF2tpa/Pzzz/Dz84OzszNkMhn69OmDuLg4rT8Szz33HG7evImLFy+2+GfjvtQ2Ndbn1qxZg/z8fOzYsQMVFRXIyspCbGwsxo0bpzbDtEpr9qXWwskIY21AVVUV/vzzT53WNvLx8cGyZctw7do1rFq1SmudmpoaREdHw9/fH3PnzoVCoUC/fv2wa9cuFBUVaZ3d19fXF3K5HA4ODpg1axaqqqqQm5sL4MFTCvHx8ZgyZQqmTp0KGxsbvP/++5BKpUhMTNTrs9bU1CAkJATx8fF6bWdokZGRcHZ2xqZNm9TK33jjDXzxxRfIy8tDZWUl9u/fj9zcXIwcORJZWVkAIDwN4eDggIiICGRlZeHOnTuYPHkylixZgn/+858a7fXo0QMAkJmZ2aKfi/tS29VYnxs5ciTCwsIQHBwMuVyOvn37oqKiAnv27NG6n9bqS63JROwAGnPmzBlhsh8mrjNnzgAAnw89qFZi1lVBQQGI6LF/yT5s06ZNOHz4MOLi4jBz5kyN97OyslBZWYnBgwerlQ8ZMgSmpqZqg+K0Uf3Vpvpr9sqVK6iurlYbmGlubg4nJye1S/W6WLNmDd566y107dpVr+0MKS0tDcnJyfjmm280Bnd269ZNuF8PAEOHDkViYiIGDBiAuLg4xMfHC+MEnnnmGbXHOj/88EN8/PHH2L17NwICAtT2qzq3qisJLYX7Utv0uD63du1a7NmzB8eOHcMLL7yAgoICrFq1Cj4+Pjh16pRafwRary+1Jr4ywlgbcO/ePQDQeXCdTCZDYmIiJBIJ3nzzTdTU1Ki9X1paCgBaF0m0sbHRuoL146gu4b///vtqc29cv35dr8GfP/zwAzIzM7Fw4UK92jekAwcOYPPmzcjIyED37t112qZfv34wNjbG1atXAQDOzs4ANFcKNzU1hZubG3JycjT2oVqWQHWuWwr3pbbncX3u9u3b2LJlC9566y2MHj0alpaWcHd3R0JCAm7duoWoqCiN/bVWX2pNbfbKyNChQ3n64zaCp6PWn2o6eF2p/nPRZ0IjHx8fLF++HNu2bcPGjRvh6uoqvGdjYwMAWn8oSktL4eLionM7AISBgTExMU1enRoA9u7di2PHjsHISPPvoIiICEREROCnn37S+CvcUHbs2IGvv/4ax48f12s164aGBjQ0NAg/8FZWVujRowcuX76sUbeurg4KhUKjvLa2FsB/z3VL4b7UOn1JV0/qc9nZ2aivr0eXLl3UyuVyOezs7IRbgw9rrb7UmvjKCGNtQOfOnSGRSPSe82Hjxo3o3bs3zp8/r1bet29fWFlZaQwIPHv2LGprazFo0CC92unWrRtkMhkuXLig13aPSkxM1Ji/o7CwEMCDS9VE1CI/HkSEsLAwZGZmIj09/bGJyLhx4zTKfvrpJxARfHx8hLKZM2fi/Pnz+OOPP4Sy6upqXL9+Xevjvqpz6+jo2JyP8kTcl1q2L+lK1z6nSuZu376tVl5RUYG7d+9q3KIBWq8vtSZORhhrAywsLODh4aH3WBPVJfZH5zKQyWQIDQ1FWloa9u3bh/LycmRmZiIoKAjOzs4IDAzUu5358+dj//79iI+PR3l5Oerr63Hjxg3hP9FZs2bB0dGx1acQ16Xdy5cvY+vWrUhISIBUKtWY6n3btm1C3Zs3b+LAgQMoLS2FUqnE6dOnsXDhQri6uiIoKEiot3z5cri5uWHevHnIzc1FcXExwsLCUFNTo3UwqOrc6jIvSXNwX2o6Q7ara59zd3eHn58fEhIScOLECdTU1CAvL084rgsWLNDYd2v1pVbVSlO96kXs6ceZOj4f+mvKdPDBwcEklUqpurpaKEtLSyNPT08CQPb29rRkyRKt265YsUJjCu+GhgaKioqiHj16kFQqJVtbW5oyZQpduXJFqBMXF0cWFhYEgHr06EE5OTm0e/duksvlBIDc3Nzo6tWrRER0//59CgsLI1dXVzIxMSEHBweaOnUqZWVlEdGDqdEB0Pr16/X63IWFhVqn8D59+jQNGzaMnJ2dhSnZnZycyNfXl7777juhni7tZmZmap3iXfWKiooS6oaGhpKnpydZWlqSiYkJubi40KJFi+jWrVsa+83Ly6PZs2eTra0tmZmZ0fPPP09Hjx7VGsOECROoa9eu1NDQoNfxacr3j/tSy/UlXfenT58rKiqikJAQ8vLyIjMzM7KysqJhw4bRv/71L63tN7UvoQ1PB8/JCHsiPh/6a0oykp2dTSYmJvTZZ5+1UFQtq76+nkaMGEF79+59KtrVR1FREclkMtq2bZve2zbl+8d9qX21q4/m9KW2nIzwbRrG2ggvLy+Eh4cjPDxc66qebVl9fT3S09NRUVHRqitHi9WuvjZs2IABAwYgODi4VdrjvtR+2tVXa/el1vJUJCNXrlzBu+++i2eeeQbW1tYwMTGBQqFAz549MWHCBJw+fVrsEAWPW5L60SXAVS9TU1N07twZo0aNQlRUFEpKSkSInBnC6tWrMX36dMyaNatdLWCWkZGB1NRUHD16VOf5Ldpzu/qIjo7GhQsXcOTIEUil0lZrl/tS+2hXH2L1pdbQ4ZORvXv3ol+/frh06RKio6ORl5eHqqoqnD9/Hhs3bkRpaWmbmcUuOzsbL774IpYvX671efupU6fijz/+gKenJxQKBYgIDQ0NKCgoQHJyMtzd3REWFoZnnnmmSdMqs7YhIiICwcHB+Oijj8QORWdjxozB559/Dicnp6eiXV0dOnQI9+/fR0ZGBmxtbVu9fe5Lbb9dXYndl1pam51nxBDOnDmDwMBAjBw5El9//TVMTP77cT08PODh4QEbGxtkZ2eLGOUDFy9eRHh4OIKCglBVVaXzAkgSiQQ2NjYYNWoURo0ahQkTJmDmzJmYMGECrl69qnW+g/aopqYGY8aMwalTp9p1G7oaO3Ysxo4dK3YYrJlee+01vPbaa6LGwH2pY2gLfakldegrI5s2bUJ9fT0++ugjtUTkYePGjcOSJUtaOTJNhlrietq0aZg3bx4KCgqwa9cuA0Yorr1792qsatke22CMMaapwyYjtbW1OHbsGDp16oTnn39e5+3IgEtl9+nTBxKJBEZGRhg0aJBw62XlypVQKBSQyWT45JNPDPaZVebNmwcAOHr0qMH3rStdjmNwcDBMTU3VLou+8847sLS0hEQiEabaDgkJQWhoKHJyciCRSODl5YXt27dDJpOhc+fOWLx4sbBqqq+vr9paGc1pAwC++uoryOVyREREtOjxYoyxp5q4T/NoZ4hHSa9evUoAaOjQoXptt379ejI1NaXPPvuMSktL6dKlSzRw4ECyt7en/Px8od7atWsJAB07dozKysqooKCARowYQZaWllRbW0tERHV1ddS9e3dydXWluro6tXaWLVtGMTExWmN44YUXqH///o3G6OnpSQqFotH3y8vLCQB169ZNn4/eqKacD12PY0BAADk6OqptGxUVRQCosLBQKJs6dSp5enqq1QsMDCRLS0u6fPky3bt3j7KysmjIkCFkbW1Nubm5Bmnj8OHDZG1tTeHh4Xp9/qY82suYNvxoPTMU8KO9ra+8vByA9sWdGmPopbKNjY2xdOlS5ObmIi0tTdimuroaqampePPNN5v5KbWztraGRCLRewErQ2nKcWwqExMT4eqLt7c34uPjUVFRofdS5I2ZMGECysvLsW7dOoPsjzHGmKYOm4yokhB9VoE09FLZALBw4UIoFArExsYKZfv27cPkyZMhl8t1jk0fqgGwLbX/J2nucWyOwYMHw8LCQu+lyBljjImnwyYj3bt3h0wmE5b81oWhl8pW7eutt97CqVOn8OOPPwIAPv744xadsEb1mXv37t1ibTxOSxxHfZiZmQkLZjHGGGv7OmwyYmZmhnHjxqGoqAgnT55stN7du3excOFCAIZfKlslODgYUqkUMTExOHHiBLp16wZPT88m7UsXX331FQBg/PjxLdbG47TUcdSFUqls8TYYY4wZVodNRoAH0+aamZlh+fLlqKmp0Vrn119/FR77NfRS2SouLi6YMWMGDh48iHXr1iEkJKRJ+9FFfn4+YmJi4OLi0mJjUp5En+NoYmKidluruTIyMkBEGDp0aIu1wRhjzLA6dDIyYMAAfP755/j1118xYsQIHDlyBGVlZVAqlfjzzz+RkJCABQsWCNPqGnqp7IeFhoairq4OJSUlGD16dLM/GxGhsrISDQ0NICIUFhYiKSkJw4YNg7GxMdLT00UbM6LPcfTy8sLdu3eRnp4OpVKJwsJCXL9+XWOfdnZ2uHXrFq5du4aKigohuWhoaEBJSQnq6upw6dIlhISEwNXVVXi8ubltHD16lB/tZYyxlibu0zzaGfpRttzcXHrvvfeoX79+ZGVlRcbGxmRjY0PPPfccLViwgE6ePCnUNfRS2Q/z8/OjPXv2aI1RlyWpv/jiC3r22WfJwsKCTE1NycjIiACQRCIhGxsbev755yk8PJyKi4sNduyImnY+dDmORETFxcXk5+dHMpmM3N3d6d1336UVK1YQAPLy8hIe0f3ll1/Izc2NzM3Nafjw4ZSfn0+BgYEklUqpa9euZGJiQnK5nCZPnkw5OTkGa+PIkSNkbW1NmzZt0uvz86O9zFD40V5mKGjDj/ZKiHScd7wVTZ8+HQCQkpIiciQMaLvnY/HixUhJSUFxcbHYoWhITk7GzJkzdZ7Wn7HGtNXvH2t/JBIJkpKSMGPGDLFDeVRKh75Nwzq++vp6sUNgjDHWTJyMMMYYY0xUnIywdmnNmjVITExEWVkZ3N3dcfDgQbFDYowx1kTal7JlrI2LjIxEZGSk2GEwxhgzAL4ywhhjjDFRcTLCGGOMMVFxMsIYY4wxUXEywhhjjDFRcTLCGGOMMVG12adpDh48CIlEInYY7CF8PvTHx4wZCvcl1pG1yengT58+jby8PLHDYIw9wenTpxEbG4ukpCSxQ2GM6cDX1xcuLi5ih/GolDaZjDDG2gdeg4cxZgC8Ng1jjDHGxMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZExckIY4wxxkTFyQhjjDHGRMXJCGOMMcZEZSJ2AIyx9qGwsBD/+te/1MrOnTsHANi9e7daubW1NWbPnt1qsTHG2jcJEZHYQTDG2r779++jc+fOqKyshLGxMQBA9d+HRCIR6imVSrzxxhv45JNPxAiTMdb+pPBtGsaYTszMzDBt2jSYmJhAqVRCqVSirq4OdXV1wr+VSiUAYM6cOSJHyxhrTzgZYYzpbM6cOaitrX1sHRsbG4wePbqVImKMdQScjDDGdObn5wcHB4dG35dKpZg7dy5MTHg4GmNMd5yMMMZ0ZmRkhICAAEilUq3vK5VKHrjKGNMbJyOMMb3Mnj1bGBvyqC5dusDHx6eVI2KMtXecjDDG9PL888/Dzc1No9zU1BRvvPGG2pM1jDGmC05GGGN6e/311zVu1dTW1vItGsZYk3AywhjTW0BAgMatGi8vL/Tr10+kiBhj7RknI4wxvfXu3Rve3t7CLRmpVIr58+eLHBVjrL3iZIQx1iR//etfhZlY6+rq+BYNY6zJOBlhjDXJ7NmzUV9fDwAYOHAg3N3dRY6IMdZecTLCGGsSV1dXvPDCCwCAN954Q+RoGGPtmcY0iadPn0Z0dLQYsTDG2pn79+9DIpHgm2++wYkTJ8QOhzHWDqSkpGiUaVwZycvLw8GDB1slIMZ0dfDgQdy4cUPsMNqVM2fO4MyZMy3ahouLCxwdHSGTyVq0HSYu/v4xQ7hx40aj+UWjC0hoy1wYE4tEIsGyZcswY8YMsUNpN6ZPnw6g5b/Lv//+O7y8vFq0DSYu/v4xQ0hOTsbMmTO1vsdjRhhjzcKJCGOsuTgZYYwxxpioOBlhjDHGmKg4GWGMMcaYqDgZYYwxxpioOBlpBdu2bUPnzp0hkUiwa9cuofzIkSNQKBT497//3eIxNDQ0ICYmBr6+vjrVX7hwIaytrSGRSHDhwgW92wsPD4e3tzfkcjnMzMzg5eWFlStXorKyUu99GVJrHnPGGGO64WSkFbz33ns4deqURjkRtUr72dnZePHFF7F8+XJUV1frtM2ePXuQkJDQ5DaPHz+OJUuW4Nq1aygqKkJkZCRiY2OFx03F0lrHnDHGmO4anWeEtbwJEyagrKysRdu4ePEiwsPDERQUhKqqqlb7MbayskJgYKCwkNqMGTOQmpqK5ORk5OXloVu3bq0Sx6Na45jrqqamBmPGjNGaqDLG2NOEr4x0IESElJQU7N69Wyjr378/UlNTERAQADMzM732p1oevikOHz4sJCIq9vb2AKDz1ZmObu/evSgoKBA7DMYYE12zk5HY2FhYWlrCyMgIgwYNgqOjI6RSKSwtLTFw4ECMGDEC3bp1g0wmg42NDVauXKm2/ffffw9vb28oFArIZDL069cPX3/9NQDgk08+gZWVFSQSCWxtbZGeno5z587Bzc0NxsbGmDNnjl6xbt++HTKZDJ07d8bixYvh7OwMmUwGX19fnD17Vq0uESE6Ohp9+vSBmZkZbG1tMXnyZPz2229NqveoH374Aa6urpBIJNi5cycAID4+HpaWlrCwsMChQ4cwfvx4yOVyuLi4YP/+/Wrb19fXIzIyEr169YK5uTns7e3h7u6OyMjIJs2SSESIiopCr169YGZmBoVCgRUrVui9n8e5efMmzM3NRVvdtTnHXNe+ExwcDFNTUzg5OQll77zzDiwtLSGRSFBUVAQACAkJQWhoKHJyciCRSISJw7766ivI5XJERES0xiFhjLG2gR6RlJREWoof64MPPiAAdPbsWaqqqqKioiJ6+eWXCQB9+eWXVFhYSFVVVRQcHEwA6MKFC8K2KSkptGHDBrp79y4VFxfT0KFDqVOnTsL7ly9fJgsLC3rjjTeEstWrV9OePXv0ilElMDCQLC0t6fLly3Tv3j3KysqiIUOGkLW1NeXm5gr11q9fT6ampvTZZ59RaWkpXbp0iQYOHEj29vaUn5+vd73s7GwCQB9//LFQlpeXRwBox44dQtnatWsJAB07dozKysqooKCARowYQZaWllRbWyvUi4iIIGNjYzp06BBVV1fTzz//TI6OjjRq1KhGP/sLL7xA/fv31/re2rVrSSKR0N/+9jcqKSmh6upqiouLIwB0/vx5/Q6yFlVVVWRtbU3BwcFN2h4AJSUlNTuO5hxzXftOQEAAOTo6qrUbFRVFAKiwsFAomzp1Knl6eqrVO3z4MFlbW1N4eHizP+u0adNo2rRpzd4PY4b6/rGn22Pyi2SD3qbx9vaGhYUFOnXqhNmzZwN4sMy4vb09LCwsMHfuXABQu2owbdo0fPDBB7C1tYWdnR0mTZqE4uJiFBYWAgD69OmDmJgYfPrpp/j888+xf/9+3L9/HwsWLGhynCYmJsKVDG9vb8THx6OiogKJiYkAHtzLj46Ohr+/P+bOnQuFQoF+/fph165dKCoqEm6D6FqvKXx9fSGXy+Hg4IBZs2ahqqoKubm5wvvp6ekYNGgQJk2aBHNXduguAAAgAElEQVRzcwwcOBCvvfYaTpw4gdraWr3aqqmpQUxMDF566SUsX74cNjY2MDc3h52dXZPjf1RkZCScnZ2xadMmg+3T0J50zIEn953mmjBhAsrLy7Fu3TqD7I8xxtqDFhvAampqCgCoq6sTyqRSKQBAqVQ2up2qTn19vVD21ltv4X//93+xePFivPTSSwZfVXjw4MGwsLAQkqSsrCxUVlZi8ODBavWGDBkCU1NT4bK8rvWaS3UsHz5u9+7d01gptb6+HlKpVGOsxpP8/vvvqK6uxpgxY5ofrBZpaWlITk7GN998A2tr6xZpw9C0HXNtHu07jDHG9Cf6ANYvv/wSo0aNgoODA8zMzDTGlKhERESgsrKyxQb8mZmZCVdjSktLATx4IuRRNjY2qKio0KteS3jllVfw888/49ChQ6ipqcG5c+eQnp6OV199Ve9kRLU0uIODg8HjPHDgADZv3oyMjAx0797d4PtvCx7uO4wxxvQnajKSm5uLKVOmwMnJCWfPnkVZWRm2bNmiUU+pVGLp0qWIjo7G6dOnDX6pX6lUorS0FC4uLgAeJBIAtCYTTanXEjZs2IDRo0dj3rx5kMvl8Pf3x4wZM5o0N4jqCsv9+/cNGuOOHTuwb98+HD9+HF26dDHovtuKR/sOY4wx/Yk6z0hmZiaUSiXefvtteHh4AND+OOm7776LRYsWwd/fHzdv3sTGjRsxduxY+Pj4GCSOjIwMEBGGDh0KAOjbty+srKxw7tw5tXpnz55FbW0tBg0apFe9lpCVlYWcnBwUFhbCxKR5p7Fv374wMjLCd999h6CgoGbHRkRYtWoVSkpKkJ6e3uz42rJH+w7wYFzJk27vMMYY+y9Rr4y4uroCAL799lvcu3cP2dnZGuMs4uLi0LVrV/j7+wN4MBDS29sbAQEBKC8vb1K7DQ0NKCkpQV1dHS5duoSQkBC4urpi3rx5AB5cKQgNDUVaWhr27duH8vJyZGZmIigoCM7OzggMDNSrXktYsmQJXF1dDTK9uoODA6ZOnYqDBw9i7969KC8vx6VLl5o8APfy5cvYunUrEhISIJVKIZFI1F7btm1rdsxieVLfAQAvLy/cvXsX6enpUCqVKCwsxPXr1zX2ZWdnh1u3buHatWuoqKiAUqnE0aNH+dFextjTR49Hb7SKjY0lCwsLAkDdu3en77//njZv3kwKhYIAkKOjI33++ed04MABcnR0JABka2tL+/fvJyKisLAwsrOzIxsbG5o+fTrt3LmTAJCnpycNGDCAJBIJ2dnZ0alTp4iIaNmyZWRkZEQASKFQ0Llz5/R6tCgwMJCkUil17dqVTExMSC6X0+TJkyknJ0etXkNDA0VFRVGPHj1IKpWSra0tTZkyha5cuaJ3vb/97W/CZ7e0tCR/f3/asWMHOTk5EQCysLCgSZMmUVxcnHAse/ToQTk5ObR7926Sy+UEgNzc3Ojq1atERHT8+HHq1KkTARBeUqmU+vTpQ6mpqULbp0+fpmHDhpGzs7NQz8nJiXx9fem7774T6lVUVNDChQupU6dOZGVlRcOHD6f169cTAHJxcaGLFy/qfIwzMzPV4nr0FRUVpdc5IzLMo4XNPea69p3i4mLy8/MjmUxG7u7u9O6779KKFSsIAHl5eQmPAf/yyy/k5uZG5ubmNHz4cMrPz6cjR46QtbU1bdq0qVmflYgf7WWGY4jvH2OPe7RXQqQ+P3hycjJmzpzZYdfwWLx4MVJSUlBcXCx2KM0SHx+P7OxsxMTECGW1tbVYtWoV4uPjUVJSAnNzcxEjNCyJRIKkpKQmTehmKO2t76jWAUpJSRE5EtbetYXvH2v/HpNfpHTcm/mP8fBjw+1Rfn4+goODNVbTNTU1haurK5RKJZRKZYdKRtqK9t53GGOsLRL90d7m+u233zTGJGh7zZo1S+xQDcbc3BxSqRR79+7FnTt3oFQqcevWLezZswfr16/HrFmzIJfLDdrm03icGWOMtY52n4z07t0bRPTE14EDB7BmzRokJiairKwM7u7uBp88rbUoFAp88803+PXXX9GzZ0+Ym5vD29sbiYmJ2Lx5Mz799FODt6nPce6IOkrf0ce3336L1atXIzU1FR4eHkLC+frrr2vUHTt2LKytrWFsbIxnnnkGv/zyiwgRN929e/fQu3dvvP/++1rfb2hoQExMDHx9fQ3S3pP2Fx4eDm9vb8jlcpiZmcHLywsrV67UOmD9n//8J4YMGQJra2u4ublh/vz5yM/PF97/4osvsGXLFtGu6nXkfqTPeQK4Hz2WHgNMGBMNeACd3pozgHX9+vU0ceJEKi8vF8o8PT2FQdOHDx/W2Obo0aP02muvNTleMS1fvpwA0Nq1azXeu3r1Kg0bNowANLq2kz502d/IkSMpLi6OiouLqby8nJKSkkgqldLLL7+sVu/AgQMEgLZs2UKlpaV0/vx58vDwoAEDBpBSqRTqxcbG0siRI6mkpKRJMTf1+9fR+5Gu54mI+xHR4wewcjLC2gVORvTX1GTko48+op49e1JNTY1auaenJ33++edkZGREXbt2pdLSUrX329OPyMNOnjxJY8eO1ZqMXLhwgfz9/Wnfvn00YMCAZv+I6Lq/CRMmUF1dnVrZjBkzCIDaoox+fn7UpUsXamhoEMpUTyT+8MMPatsHBweTj4+P2o+Lrpry/Xsa+pGu54n70QOttlAeY6x9+/3337Fu3Tp8+OGHGmsfAQ8WEwwJCcHNmzfx3nvviRChYdXU1GDFihWIjY3V+n7//v2RmpqKgIAAmJmZNbs9Xfd3+PBhjWUd7O3tAQDV1dVCWV5eHpydndUmi+zWrRsAaMxts2HDBly4cKHRz2pIT0s/0vU8cT96Mk5GGGOC7du3g4gwadKkRuts2rQJPXv2xJ49e/Dtt98+dn9EhOjoaGGlY1tbW0yePFltYcH4+HhYWlrCwsIChw4dwvjx4yGXy+Hi4oL9+/er7a++vh7r16+Hq6srzM3N8eyzzyIpKanJn3ft2rV45513WmRdJkO7efMmzM3N4e7uLpR5eHhorNelus+vmtVaxdbWFiNHjkRsbGyLT93wtPWjh2k7T21JW+1HnIwwxgRffvklevXqBQsLi0brmJub45NPPoGRkREWLVqEqqqqRutu2LABq1evxtq1a1FQUIATJ04gLy8PI0aMwJ07dwAAb7/9NpYtW4aamhpYW1sjKSkJOTk58PDwwKJFi9Sm1l+1ahW2bt2KmJgY3L59GxMnTsScOXM0lmTQxcmTJ5GTk4M5c+bovW1rq66uxvHjx7Fo0SJhRWngwcDq/Px87NixAxUVFcjKykJsbCzGjRuntkSBynPPPYebN2/i4sWLLRrv09SPHtbYeWor2nI/4mSEMQYAqKqqwp9//glPT88n1vXx8cGyZctw7do1rFq1SmudmpoaREdHw9/fH3PnzoVCoUC/fv2wa9cuFBUVaV1uwNfXF3K5HA4ODpg1axaqqqqQm5sL4METL/Hx8ZgyZQqmTp0KGxsbvP/++5BKpUhMTNTrs9bU1CAkJATx8fF6bSeWyMhIODs7aywSOnLkSISFhSE4OBhyuRx9+/ZFRUUF9uzZo3U/PXr0APBgXbCW8jT1o0c1dp7airbcjxpNRnSZU4Jf/GqtFwDMnDlT9Dja00vfx48LCgpARI/9a/ZhmzZtQq9evRAXF4cffvhB4/2srCxUVlZi8ODBauVDhgyBqampxjpUj1L95ab6i/bKlSuorq5G3759hTrm5uZwcnJSu1yvizVr1uCtt95C165d9dpODGlpaUhOTsbXX38Na2trtffWrl2L3bt349ixY6isrMQff/wBX19f+Pj4IC8vT2NfqnOruprQEp6mfvSwx52ntqCt96NGZ2A11P0zxgxh5syZCAkJMdhKzU+Dh5cK0MW9e/cAQOcBdjKZDImJiRg+fDjefPNNbNmyRe390tJSAICVlZXGtjY2NqioqNArPtVl/Pfff19jPhBnZ2ed9/PDDz8gMzMT0dHRerUvhgMHDiA6OhoZGRno0qWL2nu3b9/Gli1bsHr1aowePRoA4O7ujoSEBNja2iIqKgrbt29X20Y1K7PqXLeEp6UfPexx56ktaA/9qNFkhNcgYG3JzJkz4ePjw/1SD/quSaP6D0afSY18fHywfPlybNu2DRs3bhRW4gYe/FAA0PpjUVpaChcXF73iUw0yjYmJQUhIiF7bPmzv3r04duwYjIw0LwxHREQgIiICP/30k8Zf4q1tx44d+Prrr3H8+HGtP8TZ2dmor6/X+HGRy+Wws7NDVlaWxja1tbUA0KJLRTwt/UjlSedJbO2lH/GYEcYYAKBz586QSCQoKyvTa7uNGzeid+/eOH/+vFp53759YWVlpTEo8OzZs6itrcWgQYP0aqdbt26QyWQaazLpKzExUWPm4MLCQgAPLlcTkaiJCBEhLCwMmZmZSE9Pb/QHTvUjfPv2bbXyiooK3L17V3g082Gqc+vo6GjgqP/raelHup4nsbS3fsTJCGMMwIP7wB4eHrhx44Ze26kusz86n4FMJkNoaCjS0tKwb98+lJeXIzMzE0FBQXB2dkZgYKDe7cyfPx/79+9HfHw8ysvLUV9fjxs3bgj/kc6aNQuOjo6tPo24Idu9fPkytm7dioSEBEilUo2xQNu2bQPw4FK6n58fEhIScOLECdTU1CAvL084rgsWLNDYt+rc9uvXr9lxNuZp6Ue6nid9PNX9SI8Z0hgTDXgGVr01ZQbW4OBgkkqlVF1dLZSlpaWRp6cnASB7e3tasmSJ1m1XrFihMXNmQ0MDRUVFUY8ePUgqlZKtrS1NmTKFrly5ItSJi4sjCwsLAkA9evT4f+zde1xVVfo/8M8GzuFwOQdQUQgEuVhqWualFHXUamwcRlO8i6WVhnYh0kzN9GukluKAo0mOl6/10jJAjMpR65uNOZVaTZqGkxqT94iLICgoB3h+f/Tj5BHEc4PNgc/79eIP9157reesvQ487stakpOTI+vWrRODwSAAJDQ0VE6cOCEiIteuXZM5c+ZISEiIuLm5ib+/v4waNUqys7NFRGTkyJECQBYuXGjV587Pz69zBtb9+/dLv379JDAwUAAIAAkICJCoqCj5/PPPTeUsbdeS+o4ePWraV9dPUlKSqb6CggJJSEiQyMhIcXd3F29vb+nXr5+8//77dbYfHR0tQUFBZjNtWsLa719LGEfWnCeOo99wOnhyekxGrGdLMnLy5Elxc3OTzZs3N1BUDauqqkoGDBggGzdubBHtWqOgoEB0Op2sWLHC6mOt/f5xHDlXu9awZxxxOngiskhkZCQSExORmJh405VHm6qqqipkZWWhtLQU48ePb/btWmvRokXo3r074uPjG7wtjiPnaddaDTWOGjUZuXEJ6QULFtRbPjk5GYqiwMXFBZ06dcK+ffsaLBZFUaDRaBAUFITY2Fj85z//cVhbN1qxYoXpIa+1a9eatu/cuRM+Pj746KOPGqztGvUtPV1X3yiKAq1Wi7Zt22LQoEFISkpCUVFRg8dJjW/evHkYM2YMxo8fb/VDiGrau3cvMjMzsWvXLovnuHDmdq2RnJyMw4cPY+fOndBoNI3SJseRc7RrjQYdR1ZcRnGYmvuGAQEBUlFRUWeZyspKCQ0NFQDywAMPNGgsPj4+IiJy+fJl+fDDDyUkJES8vb3lxx9/bLB2T548KQDkzTffNG3bsWOHGAwG+fDDDxusXRHLl7K+vm+qq6ulqKhI/vnPf8qUKVNEURQJDAyUb775pkFjrQHeprGarav21vj4449lzpw5DoyI1JCVlSVLly6ttXqrNez5/nEcNQ+OGEdN8jZNz549kZubi6ysrDr3Z2ZmNvrsiF5eXhg2bBj+9re/4fLly1i9enWjth8dHY1Lly5h2LBhDdbG999/j7lz52LGjBno3r27xccpigJfX18MGjQImzZtQnp6On799VdTzM1deXl5nVeRnK0NawwZMgSvv/662mGQnR5++GHMmzev1lsqjYXjqHlo6HGkWjLy1FNPAQDefPPNOvcnJydj1qxZjRmSyb333gsA+OGHH1Rp31FEBBkZGWZrNzhqKevRo0djypQpyMvLM7vV1Fxt3Lix1qqWztgGEVFTpFoycv/996Nz58745z//iePHj5vt+/LLL1FWVoYhQ4bUeey//vUvdOnSBT4+PtDpdOjWrRs+/vhjAMBbb70Fb29vKIoCPz8/ZGVl4dtvv0VoaChcXV0tWqGzsrISgPl0xmLBEtbWlLvRF198gZCQECiKgjfeeAOA9UtiL126FHfccQc8PDzQpk0bhIWFYenSpQ02a+mUKVMAALt27WqQ+u1hyXmIj4+HVqtFQECAadvTTz8NLy8vKIqCgoICAEBCQgJmzZqFnJwcKIqCyMhIrFq1CjqdDm3btsX06dMRGBgInU6HqKgos7Uy7GkDAHbv3g2DwYAlS5Y0aH8REanKins6DhMRESE///yz/O1vfxMAkpCQYLZ/5MiRsmnTJiktLa3zmZGMjAxZtGiRXLx4UQoLC6VPnz7SunVr0/5jx46Jp6enTJ482bRt3rx5smHDhjpjqXkuosbmzZsFgMyePdu0beHChaLVamXz5s1SXFwsR44ckR49ekibNm0kNzfX6nJ1PTNy9uxZASCrV682bZs/f74AkD179silS5ckLy9PBgwYIF5eXmbP2yxZskRcXV3lgw8+kLKyMvn3v/8t7dq1k0GDBt30PNx3330WPzNSl5KSEgEg7du3v2kZR4GV96wtPQ+xsbHSrl07s2OTkpIEgOTn55u2jRo1SiIiIszKxcXFiZeXlxw7dkyuXr0q2dnZ0rt3b9Hr9XLmzBmHtLFjxw7R6/WSmJho8WevYe8zI0Q1rP3+EdWlST4zAgCTJ0+Gl5cX3n77bZSXlwMA/vvf/+Kbb76p9wrG6NGj8T//8z/w8/NDq1atMHz4cBQWFpqmdO7cuTNSUlLw9ttv45133sHWrVtx7dq1OmeSu96VK1eQmZmJF154AW3btsVzzz0HwPIlrG1Z6tpS9S2JDQBZWVno2bMnhg8fDg8PD/To0QMPP/ww9u3bZ1pHwNH0ej0URbF6oaqG1pDn4UZubm6mqy9dunRBamoqSktL7V6KvEZ0dDRKSkpu+eYZEZEzUzUZ8fHxwcSJE1FUVIT33nsPwG+LFz311FOmZZ8tUfOK0fULMz355JMYPXo0pk+fjvT0dCxfvvymx1+6dAmKosDHxwfPPfcc/vznP+Prr782PUBr6RLW9i51bakbl8QGfls9UUTMylVVVUGj0TTYA0dXrlyBiMBgMDRI/bZqrPNQl169esHT09OupciJiFoa1Sc9q3mQde3atSguLkZGRgamT59e7zH/+Mc/MGjQIPj7+8Pd3R0vvvhineWWLFmCy5cv3/KhQB8fH4gIKisrce7cOfzv//4vQkNDTfstXcLa0UtdW+PPf/4z/v3vf+ODDz5AeXk5vv32W2RlZeEvf/lLgyUjJ06cAAB06tSpQeq3lZrnAfjtWaOaq3RERHRrqicj3bt3R58+ffD1118jLi4OY8aMgZ+f303LnzlzBiNHjkRAQAAOHjyIS5cuYdmyZbXKGY1GPPfcc0hOTsb+/fuxePFim2O0dAlrRy91bY1Fixbh/vvvx5QpU2AwGBATE4OxY8di/fr1Ddbm7t27AQBDhw5tsDZsoeZ5MBqNDd4GEVFz46Z2AMBvV0cOHDiAbdu24eTJk/WWPXr0KIxGI5566imEh4cD+G0OjBs9++yzmDZtGmJiYnD+/Hm8+uqrGDJkCPr27Wt1fJYuYe3opa6tkZ2djZycHOTn58PNreFPa25uLlJSUhAcHIzHH3+8wduzhjXnwc3Nzex2l7327t0LEUGfPn0arA0iouZG9SsjADB27Fi0adMGI0eONCUYNxMSEgIA+PTTT3H16lWcPHmy1jMAa9asQVBQEGJiYgAAS5cuRZcuXRAbG4uSkhKr47N0CWtHL3VtjWeeeQYhISEOXwdCRHD58mVUV1dDRJCfn4+0tDT069cPrq6uyMrKanLPjFhzHiIjI3Hx4kVkZWXBaDQiPz8fp0+frlVnq1atcOHCBZw6dQqlpaWm5KK6uhpFRUWorKzEkSNHkJCQgJCQENNrz/a2sWvXLr7aS0TNnxWv3titviWkX3zxRfnqq69M/3755ZclICBAAIiLi4t06dJF/vWvf4mIyJw5c6RVq1bi6+srY8aMkTfeeEMASEREhHTv3l0URZFWrVqZ6nv++efFxcVFAIiPj498++238uWXX8rtt99uWk45MDBQxowZc9PYLVnC2tJyf/3rX6Vdu3YCQLy8vCQmJkZWr15t+ryenp4yfPhwq5bE/uyzz6R169ZmS0RrNBrp3LmzZGZmmtq2ZOnpDz/8UO666y7x9PQUrVZr6jtFUcTX11fuvfdeSUxMlMLCQluHgtVg5auFlp6vwsJCGTx4sOh0OgkLC5Nnn31WZs+eLQAkMjLS9Irud999J6GhoeLh4SH9+/eX3NxciYuLE41GI0FBQeLm5iYGg0FGjBghOTk5Dmtj586dotfrZfHixVb3GV/tJUex9vtHVJf6Xu1VRMxfwUhPT8e4ceNqvZlBTVtqaipOnjyJlJQU07aKigrMnTsXqampKCoqgoeHh4oR2kdRFKSlpTXYBG62mD59OjIyMlBYWKh2KHUaM2YMACAjI0PlSMjZNcXvHzmfevKLjCbxzAjZJzc3F/Hx8Th8+LDZdq1Wi5CQEBiNRhiNRqdORpqq618nJyIi2zSJZ0bIPh4eHtBoNNi4cSN+/fVXGI1GXLhwARs2bMDChQsxfvz4JvdcBxERUQ0mI82Aj48PPvnkE/zwww+4/fbb4eHhgS5dumDTpk14/fXX8fbbb6sdYrPz0ksvYdOmTbh06RLCwsKwbds2tUMiInJavE3TTAwYMAD/93//p3YYLcbSpUuxdOlStcMgImoWeGWEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVHXTB1jT09MbMw6iW9q/f7/aITiVc+fOAeB3mRyD3z+yV31j6KYzsBIRERE5Wl0zsNZKRoiILMXlI4jIATL4zAgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREanKTe0AiMg5nDt3DpMnT0ZVVZVpW1FREfR6PQYNGmRW9o477sDf//73Ro6QiJwVkxEiskhwcDBOnz6NnJycWvs+//xzs3//4Q9/aKywiKgZ4G0aIrLYo48+Co1Gc8ty48ePb4RoiKi5YDJCRBaLjY1FZWVlvWXuvPNOdOnSpZEiIqLmgMkIEVksIiICd911FxRFqXO/RqPB5MmTGzkqInJ2TEaIyCqPPvooXF1d69xXWVmJMWPGNHJEROTsmIwQkVUmTJiA6urqWttdXFzQp08fdOjQofGDIiKnxmSEiKwSGBiIfv36wcXF/NeHi4sLHn30UZWiIiJnxmSEiKz2yCOP1NomIoiJiVEhGiJydkxGiMhqo0ePNntuxNXVFQ8++CDatm2rYlRE5KyYjBCR1fz8/PDHP/7RlJCICCZNmqRyVETkrJiMEJFNJk2aZHqQVaPRYMSIESpHRETOiskIEdlk+PDhcHd3BwAMGzYM3t7eKkdERM6KyQgR2cTLy8t0NYS3aIjIHoqIiNpBWONmMz8SERHRbw+YZ2RkqB2GNTKcctXehIQE9O3bV+0wmpX9+/dj5cqVSEtLUzsUpzJu3LgWPR6rqqqQlpaGiRMnqh2KU+P3jxwlJSVF7RBs4pRXRtLS0jB27Fi1Q2lW0tPTMW7cODjZcFAdxyNw9epV6HQ6tcNwavz+kaPULMfgbFdG+MwIEdmFiQgR2YvJCBEREamKyQgRERGpiskIERERqYrJCBEREamqxSYjU6dOhV6vh6IoOHz4sNrhNBs7d+6Ej48PPvroI7VDISIiJ9Fik5ENGzZg/fr1aofR7PDVRCIislaLTUaam/LyckRFRakdBqKjo3Hp0iUMGzZM7VCaTJ8QEVH9WnQy0pymlt+4cSPy8vLUDqNJYZ8QETmHFpOMiAiSkpJwxx13wN3dHT4+Ppg9e7ZZmeXLl8PT0xN6vR55eXmYNWsWgoKCcPz4cYgIkpOT0blzZ7i7u8PPzw8jRozAjz/+aDp+1apV0Ol0aNu2LaZPn47AwEDodDpERUXh4MGDteK5VX3x8fHQarUICAgwbXv66afh5eUFRVFQUFAA4Lfp8WfNmoWcnBwoioLIyMiG6MJb+uKLLxASEgJFUfDGG28AAFJTU+Hl5QVPT0988MEHGDp0KAwGA4KDg7F161bTsZb2nb19snv3bhgMBixZsqQxuoSIiCwhTgaApKWlWX3c/PnzRVEU+etf/ypFRUVSVlYma9asEQBy6NAhs3IA5LnnnpPVq1dLTEyM/Oc//5GFCxeKVquVzZs3S3FxsRw5ckR69Oghbdq0kdzcXNPxcXFx4uXlJceOHZOrV69Kdna29O7dW/R6vZw5c8ZUztL6YmNjpV27dmafJSkpSQBIfn6+aduoUaMkIiLC6n6pkZaWJo4YDmfPnhUAsnr1atO2mj7ds2ePXLp0SfLy8mTAgAHi5eUlFRUVpnKW9p09fbJjxw7R6/WSmJho92cVsX08El3PUd8/otGjR8vo0aPVDsNa6S3iykh5eTlSUlLw4IMPYubMmfD19YWHhwdatWp108l7/gYAACAASURBVGNef/11PPPMM8jMzERoaCiSk5MRExODSZMmwcfHB926dcPatWtRUFCAdevWmR3r5uZmuuLRpUsXpKamorS0FJs2bTLFY019zUVUVBQMBgP8/f0xfvx4XLlyBWfOnDErc6u+s1d0dDRKSkqwYMECh9RHRET2axHJyE8//YSysjI88MADNh2fnZ2Ny5cvo1evXmbbe/fuDa1WW+sWzI169eoFT09P0y0Ye+trDrRaLQDAaDTWW+7GviMiouanRSQj586dAwD4+/vbdHxxcTEAwNvbu9Y+X19flJaW3rIOd3d35OfnO6y+luT6viMiouanRSQjNauKXrt2zabjfX19AaDOJKG4uBjBwcH1Hm80Gs3K2VtfS3Jj3xERUfPTIpKRrl27wsXFBZ9//rnNx3t7e+Pbb781237w4EFUVFSgZ8+e9R6/d+9eiAj69OljdX1ubm63vJXRnN3YdwD7hIiouWkRyYi/vz9GjRqFbdu2YePGjSgpKcGRI0csflBUp9Nh1qxZ2L59O7Zs2YKSkhIcPXoUM2bMQGBgIOLi4szKV1dXo6ioCJWVlThy5AgSEhIQEhKCKVOmWF1fZGQkLl68iKysLBiNRuTn5+P06dO1YmzVqhUuXLiAU6dOobS01Gn/WN+q7wD7+mTXrl18tZeIqKlR+30ea8HGVylLS0tl6tSp0rp1a/H29pb+/fvLwoULBYAEBwfL999/L8uWLRMPDw8BIO3bt5fNmzebjq+urpakpCTp2LGjaDQa8fPzk5EjR8rx48fN2omLixONRiNBQUHi5uYmBoNBRowYITk5OWblLK2vsLBQBg8eLDqdTsLCwuTZZ5+V2bNnCwCJjIw0vfL63XffSWhoqHh4eEj//v3NXg+2hCNeLVy9erUEBAQIAPH09JThw4fLmjVrxNPTUwBIx44dJScnR9atWycGg0EASGhoqJw4cUJELO87e/pk586dotfrZfHixXZ91hq2jkei6/HVXnIUZ321VxFxrsVEFEVBWloaxo4dq3YodZo+fToyMjJQWFiodihWSU9Px7hx41RdW8YZ+66pj0dyDk3h+0fNw5gxYwAAGRkZKkdilYwWcZumsVVVVakdgtNi3xERtTxMRohU8umnn2LevHnIzMxEeHg4FEWBoih45JFHapUdMmQI9Ho9XF1dceedd+K7775TIWLLJSYmokuXLjAYDHB3d0dkZCRefPFFXL58uc7y1dXVSElJcdjChreqz5r43n33XfTu3Rt6vR6hoaF47LHHkJuba9r/4YcfYtmyZaom0hxLv+NYclLq3iayHprwPfp58+aJVqsVANKhQwfJyMhQOySLqX3P2ln7ztbxuHDhQhk2bJiUlJSYtkVEREjr1q0FgOzYsaPWMbt27ZKHH37Yrngby8CBA2XNmjVSWFgoJSUlkpaWJhqNRv70pz/VKnvixAnp16+fAJC7777b7rYtqc/S+N577z0BIMuWLZPi4mI5dOiQhIeHS/fu3cVoNJrKrVy5UgYOHChFRUU2xWzP949j6XccS877zAiTERIR9ZMRZ2XLeHzttdfk9ttvl/LycrPtERER8s4774iLi4sEBQVJcXGx2X5n+gMSHR0tlZWVZtvGjh0rAMzWGTp8+LDExMTIli1bpHv37nb/AbG0PkvjGzx4sNx2221SXV1t2vbGG28IAPniiy/Mjo+Pj5e+ffua/WGxlK3fP44ljqUbOWsywts0RI3op59+woIFC/DKK6+YJuO7XlRUFBISEnD+/Hm88MILKkToGDt27ICrq6vZtjZt2gAAysrKTNvuvvtuZGZmIjY2Fu7u7na3a2l9lsZ39uxZBAYGQlEU07b27dsDQK3XyRctWoTDhw9j5cqVdn8OS3AscSw1J0xGiBrRqlWrICIYPnz4TcssXrwYt99+OzZs2IBPP/203vpEBMnJyabFBf38/DBixAiztXxSU1Ph5eUFT09PfPDBBxg6dCgMBgOCg4OxdetWs/qqqqqwcOFChISEwMPDA3fddRfS0tLs+9D/3/nz5+Hh4YGwsDCH1OdodcUXHh6OvLw8s3I19/jDw8PNtvv5+WHgwIFYuXJlo7wVw7HEsdScMBkhakT/+Mc/cMcdd8DT0/OmZTw8PPDWW2/BxcUF06ZNw5UrV25adtGiRZg3bx7mz5+PvLw87Nu3D2fPnsWAAQPw66+/AgCeeuopPP/88ygvL4der0daWhpycnIQHh6OadOmmU2QN3fuXCxfvhwpKSn45ZdfMGzYMEycOLHWbMHWKisrw2effYZp06aZFklsSm4W30svvYTc3FysXr0apaWlyM7OxsqVK/HQQw+ZzQpc45577sH58+fx/fffN3jMHEscS80JkxGiRnLlyhX8/PPPiIiIuGXZvn374vnnn8epU6cwd+7cOsuUl5cjOTkZMTExmDRpEnx8fNCtWzesXbsWBQUFdc4wHBUVBYPBAH9/f4wfPx5XrlzBmTNnAABXr15FamoqRo4ciVGjRsHX1xcvv/wyNBoNNm3aZNdnX7p0KQIDA7F48WK76mkoN4tv4MCBmDNnDuLj42EwGNC1a1eUlpZiw4YNddbTsWNHAMDRo0cbNF6OJY6l5sZN7QBssX//frVDaHZq+jQ9PV3lSJqvvLw8iEi9/5O93uLFi7Fjxw6sWbMG48aNq7U/Ozsbly9fRq9evcy29+7dG1qtFgcPHqy3/pr/tdX8b/b48eMoKytD165dTWU8PDwQEBBgdqneWtu3b0d6ejo++eQT6PV6m+tpKPXFN3/+fGzYsAF79uzBfffdh7y8PMydOxd9+/bFV199ZbrnX6Pm3NZcSWgoHEscS82NUyYjK1eubFEP9jSmun5RkWNcvXoVACx+uE6n02HTpk3o378/Hn/8cSxbtsxsf3FxMQDA29u71rG+vr51rgpdn5pL+C+//DJefvlls32BgYFW1VXjvffeQ3JyMvbu3YvbbrvNpjoaUn3x/fLLL1i2bBnmzZuH+++/HwAQFhaG9evXw8/PD0lJSVi1apXZMR4eHgB+P9cNhWOJY6m5ccrbNGlpaRAR/jjwp+bBMrXjcLYfa9T8crFmQqO+ffti5syZOHnyJF599VWzfb6+vgBQ5x+K4uJiBAcHWxWfv78/ACAlJaXW57TlauTq1auxZcsWfPbZZ03yj8et4jt58iSqqqpq7TMYDGjVqhWys7NrHVNRUQHg93PdUDiWmhZnHktNhVNeGSFyRm3btoWiKLh06ZJVx7366qvYsWMHDh06hJCQENP2rl27wtvbu9YDgQcPHkRFRQV69uxpVTvt27eHTqfD4cOHrTruRiKCuXPnoqioCFlZWXBza1q/ZiyNr+YP8C+//GK2vbS0FBcvXqx1WR2A6dy2a9fOwVGb41hqGprDWGoqnPLKCJEz8vT0RHh4OM6dO2fVcTWX2G+cy0Cn02HWrFnYvn07tmzZgpKSEhw9ehQzZsxAYGAg4uLirG7nsccew9atW5GamoqSkhJUVVXh3Llzpl+i48ePR7t27eqdQvzYsWNYvnw51q9fD41GY5qavOZnxYoVVsVlabuWsjS+sLAwDB48GOvXr8e+fftQXl6Os2fPmvr1iSeeqFV3zbnt1q2b3XHWh2OJY6nZEScDzsDaIDgDq22sHY/x8fGi0WikrKzMtG379u0SEREhAKRNmzbyzDPP1Hns7Nmza82aWV1dLUlJSdKxY0fRaDTi5+cnI0eOlOPHj5vKrFmzRjw9PQWAdOzYUXJycmTdunViMBgEgISGhsqJEydEROTatWsyZ84cCQkJETc3N/H395dRo0ZJdna2iIiMHDlSAMjChQtv+hmPHj0qAG76k5SUZCq7f/9+6devnwQGBpr2BwQESFRUlHz++eemcpa0a2l91sRXUFAgCQkJEhkZKe7u7uLt7S39+vWT999/v872o6OjJSgoyGyWTUvY8v3jWOJYqouzzsDqdH99mIw0DCYjtrF2PJ48eVLc3Nxk8+bNDRhVw6mqqpIBAwbIxo0bW0S71igoKBCdTicrVqyw+lhbvn8cS87VrjXsGUvOmozwNg1RI4qMjERiYiISExNvuupoU1VVVYWsrCyUlpZi/Pjxzb5day1atAjdu3dHfHx8o7THseQ87VqrscdSU8BkhKiRzZs3D2PGjMH48eOtfgBRTXv37kVmZiZ27dpl8fwWztyuNZKTk3H48GHs3LkTGo2m0drlWHKOdq2h1lhSW7NORjIzMxEeHl7roSKtVou2bdti0KBBSEpKQlFRkdqhUguzZMkSxMfH47XXXlM7FIs98MADeOeddxAQENAi2rXUBx98gGvXrmHv3r3w8/Nr9PY5lpp+u5ZSeyypqVknI6NGjcJ///tfREREwMfHByKC6upq5OXlIT09HWFhYZgzZw7uvPNOu9dLILLWkCFD8Prrr6sdBtnp4Ycfxrx582q9odKYOJaah6YwltTSrJORuiiKAl9fXwwaNAibNm1Ceno6fv31V0RHRzvVZc6bKS8vR1RUlNph2KQxYnfm/iEiaq5aXDJyo9GjR2PKlCnIy8vD2rVr1Q7Hbhs3bqy1TLWzaIzYnbl/iIiaqxafjADAlClTAAC7du0CACxfvhyenp7Q6/XIy8vDrFmzEBQUhOPHj0NEkJycjM6dO8Pd3R1+fn4YMWKE2eJPq1atgk6nQ9u2bTF9+nQEBgZCp9MhKiqq1oJTltQXHx8PrVZrdp/z6aefhpeXFxRFQUFBAQAgISEBs2bNQk5ODhRFQWRkZEN1WaPEbmk/2ts/u3fvhsFgwJIlSxq0v4iI6CbUfbXYerBhnpGIiAjx8fG56f6SkhIBIO3btzdtmz9/vgCQ5557TlavXi0xMTHyn//8RxYuXCharVY2b94sxcXFcuTIEenRo4e0adNGcnNzTcfHxcWJl5eXHDt2TK5evSrZ2dnSu3dv0ev1cubMGVM5S+uLjY2Vdu3amcWdlJQkACQ/P9+0bdSoURIREWFV/4jYNs9BY8RuaT/a08aOHTtEr9dLYmKiVZ9fhPPekGNwnh9yFM4z4sT0ej0URalzkajXX38dzzzzDDIzMxEaGork5GTExMRg0qRJ8PHxQbdu3bB27VoUFBRg3bp1Zse6ubmZrhp06dIFqampKC0txaZNmwD89vyCNfU1JY0Z+6360V7R0dEoKSnBggULHFIfERFZh8kIflvuWkRgMBjqLZednY3Lly+jV69eZtt79+4NrVZb6xbMjXr16gVPT0/TbQx761OTmrHf2I9EROTcmIwAOHHiBACgU6dO9ZYrLi4GAHh7e9fa5+vrW+eVlRu5u7sjPz/fYfWpRe3Yr+9HIiJybkxG8NsDjAAwdOjQesv5+voCQJ1/aIuLi03LRN+M0Wg0K2dvfWpSM/Yb+5GIiJxbi09GcnNzkZKSguDgYDz++OP1lu3atSu8vb1rTZB28OBBVFRUoGfPnvUev3fvXogI+vTpY3V9bm5uMBqN1ny0BqVm7Df2Y0O0QUREjafFJCMigsuXL6O6uhoigvz8fKSlpaFfv35wdXVFVlbWLZ8Z0el0mDVrFrZv344tW7agpKQER48exYwZMxAYGIi4uDiz8tXV1SgqKkJlZSWOHDmChIQEhISEmF4ltqa+yMhIXLx4EVlZWTAajcjPz8fp06drxdiqVStcuHABp06dQmlpaYP9gW7M2G/Vj/a2sWvXLr7aS0SkJlVf5rEBrHiV8sMPP5S77rpLPD09RavViouLiwAQRVHE19dX7r33XklMTJTCwkKz45YtWyYeHh6m132vX6K7urpakpKSpGPHjqLRaMTPz09Gjhwpx48fN6sjLi5ONBqNBAUFiZubmxgMBhkxYoTk5OSYlbO0vsLCQhk8eLDodDoJCwuTZ599VmbPni0AJDIy0vSa63fffSehoaHi4eEh/fv3N3vFtj62vFrYGLFb2o/2tLFz507R6/WyePFiqz6/CF/tJcfgq73kKM76aq8iIqJaJmQDRVGQlpaGsWPHqh1KvaZPn46MjAwUFhaqHYpF0tPTMW7cODS14dDU+9FZxiM1bU31+0fOZ8yYMQCAjIwMlSOxSkaLuU2jhqqqKrVDaBbYj0REzRuTESIiIlIVk5EG8NJLL2HTpk24dOkSwsLCsG3bNrVDckrsRyKilsFN7QCao6VLl2Lp0qVqh+H02I9ERC0Dr4wQERGRqpiMEBERkaqYjBAREZGqmIwQERGRqpzyAdaUlBRnm9ClyTt37hyA3yfMIctxPJK9+P0jRzlw4IDZul3OwulmYOWXlajpyM3NxaFDh2654jURNZ6+ffti5syZaodhjQynS0aIqOngNOZE5ACcDp6IiIjUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVOWmdgBE5ByMRiMuX75stu3KlSsAgKKiIrPtiqLA19e30WIjIufGZISILHLx4kUEBQWhqqqq1r5WrVqZ/Xvw4MH47LPPGis0InJyvE1DRBZp164d/vCHP8DFpf5fG4qiYMKECY0UFRE1B0xGiMhijzzyyC3LuLq6IiYmphGiIaLmgskIEVls1KhRcHO7+d1dV1dX/OlPf0Lr1q0bMSoicnZMRojIYgaDAUOHDr1pQiIimDRpUiNHRUTOjskIEVll0qRJdT7ECgBarRZ/+ctfGjkiInJ2TEaIyCp/+ctf4OnpWWu7RqPByJEj4eXlpUJUROTMmIwQkVV0Oh1iYmKg0WjMthuNRsTGxqoUFRE5MyYjRGS1iRMnwmg0mm0zGAz44x//qFJEROTMmIwQkdUefPBBs4nONBoNJkyYAK1Wq2JUROSsmIwQkdXc3NwwYcIE060ao9GIiRMnqhwVETkrJiNEZJMJEyaYbtW0a9cO/fv3VzkiInJWTEaIyCZRUVEICgoCADz66KO3nCaeiOhmnGahvHPnzuGrr75SOwwiuk7v3r1x/vx5tG7dGunp6WqHQ0TXGTt2rNohWEwREVE7CEukp6dj3LhxaodBRETkFJzkzzsAZDjNlZEaTtS5zVpNcsjzYR1FUZCWluZU/2O5lW3btmH06NFqh9Gi8PtH9XHG/7zzJi8R2YWJCBHZi8kIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREamKyYiKqqurkZKSgqioKIvKT506FXq9Hoqi4PDhw1a3t2zZMnTq1AkeHh7w8vJCp06dsGDBApSUlFhdl6Ps3LkTPj4++Oijj1SLgYiI1MVkRCUnT57EH/7wB8ycORNlZWUWHbNhwwasX7/e5jb/9a9/Ydq0aThz5gx+/fVXvPrqq1i2bJmqr2ZyngQiInK6Sc+ag++//x6JiYmYMWMGrly50mh/kLVaLZ5++mnodDoAwJgxY5CRkYGMjAz88ssvCAwMbJQ4rhcdHY1Lly41ert1KS8vxwMPPMBlB4iIGhmvjKjg7rvvRmZmJmJjY+Hu7m7VsYqi2Nzu9u3bTYlIjZqFzi5fvmxzvc3Fxo0bkZeXp3YYREQtTrNPRjZv3oxevXpBp9PBy8sLHTp0wKuvvgrgt1sEycnJ6Ny5M9zd3eHn54cRI0bgxx9/NB2fmpoKLy8veHp64oMPPsDQoUNhMBgQHByMrVu3msp17twZiqLAxcUFPXv2NN16efHFF+Hj4wOdToe33nrLqthFBElJSbjjjjvg7u4OHx8fzJ492/5Ouc7Jkyfh6+uL0NBQh9ZriS+++AIhISFQFAVvvPEGAMv7e9WqVdDpdGjbti2mT5+OwMBA6HQ6REVF4eDBg6Zy8fHx0Gq1CAgIMG17+umn4eXlBUVRUFBQAABISEjArFmzkJOTA0VREBkZCQDYvXs3DAYDlixZ0hhdQkTUMomTSEtLE2vDTUlJEQDy2muvSWFhoVy8eFH+/ve/S2xsrIiILFy4ULRarWzevFmKi4vlyJEj0qNHD2nTpo3k5uaa6pk/f74AkD179silS5ckLy9PBgwYIF5eXlJRUSEiIpWVldKhQwcJCQmRyspKszief/55SUlJqTPG++67T+6+++46982fP18URZG//vWvUlRUJGVlZbJmzRoBIIcOHbKqL65XUVEh586dk9WrV4u7u7ts3rzZ6jpsOR91OXv2rACQ1atXm7ZZ0t8iInFxceLl5SXHjh2Tq1evSnZ2tvTu3Vv0er2cOXPGVC42NlbatWtn1m5SUpIAkPz8fNO2UaNGSUREhFm5HTt2iF6vl8TERLs/q4gIAElLS3NIXdRyOer7R82TE46P9GZ7ZcRoNOKVV17B4MGDMXfuXLRq1Qp+fn544okn0Lt3b5SXlyM5ORkxMTGYNGkSfHx80K1bN6xduxYFBQVYt25drTqjoqJgMBjg7++P8ePH48qVKzhz5gwAwNXVFc899xzOnDmD7du3m44pKytDZmYmHn/8caviLy8vR0pKCh588EHMnDkTvr6+8PDwQKtWrezrGADt27dHcHAwFi1ahOXLlzfZBZXq6+8abm5upitbXbp0QWpqKkpLS7Fp0yaHxBAdHY2SkhIsWLDAIfUREVFtzTYZOXLkCIqLi/HQQw+Zba9JGrKzs3H58mX06tXLbH/v3r2h1WrNLvXXRavVAvgt6akxdepU+Pj4YOXKlaZtW7ZswYgRI2AwGKyK/6effkJZWRkeeOABq46zxNmzZ5GXl4d3330Xb7/9Nu65554m/6xEXf1dl169esHT09PsVhsRETVtzTYZqZk7w9fXt879xcXFAABvb+9a+3x9fVFaWmp1m97e3njyySfx1Vdf4euvvwYAvPnmm4iPj7e6rnPnzgEA/P39rT72VjQaDfz9/TFkyBC89957yM7OxtKlSx3ejlrc3d2Rn5+vdhhERGShZpuM3HbbbQBgekDxRjVJSl1JR3FxMYKDg21qNz4+HhqNBikpKdi3bx/at2+PiIgIq+upeevl2rVrNsVhqcjISLi6uiI7O7tB22ksRqPRrvNHRESNr9kmIx06dECrVq3wySef1Lm/a9eu8Pb2xrfffmu2/eDBg6ioqEDPnj1tajc4OBhjx47Ftm3bsGDBAiQkJNhUT9euXeHi4oLPP//cpuNvVFhYiIkTJ9bafvLkSVRVVaF9+/YOaUdte/fuhYigT58+pm1ubm63vL1DRETqabbJiLu7O1566SXs27cP8fHxOH/+PKqrq1FaWopjx45Bp9Nh1qxZ2L59O7Zs2YKSkhIcPXoUM2bMQGBgIOLi4mxue9asWaisrERRURHuv/9+m+rw9/fHqFGjsG3bNmzcuBElJSU4cuRInQ/WWsLLywuffPIJPvvsM5SUlMBoNOLQoUOYPHkyvLy8MHPmTJvqVVt1dTWKiopQWVmJI0eOICEhASEhIZgyZYqpTGRkJC5evIisrCwYjUbk5+fj9OnTtepq1aoVLly4gFOnTqG0tBRGoxG7du3iq71ERA1N7fd5LGXrq0pvvPGGdOvWTXQ6neh0OrnnnntkzZo1IiJSXV0tSUlJ0rFjR9FoNOLn5ycjR46U48ePm45fs2aNeHp6CgDp2LGj5OTkyLp168RgMAgACQ0NlRMnTtRqd/DgwbJhw4Y6Y9q/f7/069dPAgMDBYAAkICAAImKipLPP//cVK60tFSmTp0qrVu3Fm9vb+nfv78sXLhQAEhwcLB8//33VvXF8OHDJSwsTLy9vcXd3V0iIiJk/PjxcvToUavqEXHMq2OrV6+WgIAAASCenp4yfPhwq/o7Li5ONBqNBAUFiZubmxgMBhkxYoTk5OSYtVNYWCiDBw8WnU4nYWFh8uyzz8rs2bMFgERGRppeA/7uu+8kNDRUPDw8pH///pKbmys7d+4UvV4vixcvtuuz1gBf7SUHcMJXN6kROeH4SFdEnGNxkPT0dIwbN45rmTQRTeF8TJ8+HRkZGSgsLFQtBmspioK0tDSMHTtW7VDIiTWF7x81XU44PjKa7W0aahmqqqrUDoGIiOzEZMSJ/fjjj1AU5ZY/48ePVztUcoBPP/0U8+bNQ2ZmJsLDw03n95FHHqlVdsiQIdDr9XB1dcWdd96J7777ToWILZeYmIguXbrAYDDA3d0dkZGRePHFF2+6ZlJ1dTVSUlIQFRXlkPZvVZ818b377rvo3bs39Ho9QkND8dhjjyE3N9e0/8MPP8SyZctUTaQ5ln7nyLFkNBqxdOlSREZGQqvVwtfXF127dsWpU6dueszVq1fRqVMnvPzyy6ZtTWGMNDo1bxJZwwnvgTVrap+PefPmiVarFQDSoUMHycjIUC0Wa8DGZ0YWLlwow4YNk5KSEtO2iIgIad26tQCQHTt21Dpm165d8vDDD9sVb2MZOHCgrFmzRgoLC6WkpETS0tJEo9HIn/70p1plT5w4If369RMAN11KwRqW1GdpfO+9954AkGXLlklxcbEcOnRIwsPDpXv37mI0Gk3lVq5cKQMHDpSioiKbYrbn+8ex9DtHj6WRI0fKHXfcIQcOHBCj0SgXLlyQ4cOH1/tc3syZMwWAzJ8/32y7PWNE7d/PNkh3mmidsHObNZ4P29iSjLz22mty++23S3l5udn2iIgIeeedd8TFxUWCgoKkuLjYbL8z/QGJjo6utabT2LFjBYDZOkOHDx+WmJgY2bJli3Tv3t3uPyCW1mdpfIMHD5bbbrtNqqurTdveeOMNASBffPGF2fHx8fHSt29fsyTFUrZ+/ziWGm4sbd26VRRFkSNHjlh8zJdffilDhgypMxkRsX2MTIQ78wAAIABJREFUOOHv5+a7Ng1Rc/DTTz9hwYIFeOWVV0wT4V0vKioKCQkJOH/+PF544QUVInSMHTt2wNXV1WxbmzZtAMC0AjYA3H333cjMzERsbCzc3d3tbtfS+iyN7+zZswgMDISiKKZtNXP43Pg6+aJFi3D48GGz5SMaEsdSw46lN998Ez169EC3bt0sKl9eXo7Zs2fXe/4be4yoickIURO2atUqiAiGDx9+0zKLFy/G7bffjg0bNuDTTz+ttz4RQXJysmlxQT8/P4wYMcJsLZ/U1FR4eXnB09MTH3zwAYYOHQqDwYDg4GBs3brVrL6qqiosXLgQISEh8PDwwF133YW0tDT7PvT/d/78eXh4eCAsLMwh9TlaXfGFh4fXWuep5nmR8PBws+1+fn4YOHAgVq5c2ShvPXAsNdxYqqiowIEDB9C9e3eLj5k/fz6efvrpepf8aOwxoiYmI0RN2D/+8Q/ccccd8PT0vGkZDw8PvPXWW3BxccG0adNw5cqVm5ZdtGgR5s2bh/nz5yMvLw/79u3D2bNnMWDAAPz6668AgKeeegrPP/88ysvLodfrkZaWhpycHISHh2PatGlms9nOnTsXy5cvR0pKCn755RcMGzYMEydOrDWzsbXKysrw2WefYdq0aaZFEpuSm8X30ksvITc3F6tXr0ZpaSmys7OxcuVKPPTQQ2azAte45557cP78eXz//fcNHjPHUsONpQsXLqCiogL//ve/MXjwYAQGBkKn06Fz585Ys2ZNrUTiyy+/RE5OTp2zYt+oMceImpiMEDVRV65cwc8//2zR2kZ9+/bF888/j1OnTmHu3Ll1likvL0dycjJiYmIwadIk+Pj4oFu3bli7di0KCgrqnN03KioKBoMB/v7+GD9+PK5cuYIzZ84A+O0tgNTUVIwcORKjRo2Cr68vXn75ZWg0GmzatMmuz7506VIEBgZi8eLFdtXTUG4W38CBAzFnzhzEx8fDYDCga9euKC0txYYNG+qsp2PHjgCAo0ePNmi8HEsNO5Zq3tTx9/fHkiVLkJ2djV9//RUjRozAM888g3fffddUtry8HAkJCUhNTbWo7sYaI2pzUzsAa40ZM0btEAi/ryrM89Fw8vLyICL1/k/2eosXL8aOHTuwZs0ajBs3rtb+7OxsXL58Gb169TLb3rt3b2i1Whw8eLDe+mv+V1nzv9njx4+jrKwMXbt2NZXx8PBAQECA2aV6a23fvh3p6en45JNPoNfrba6nodQX3/z587Fhwwbs2bMH9913H/Ly8jB37lz07dsXX331Va01oGrObc2VhIbCsdSwY6nmmZM777zT7BXhV155BW+++SbWrVuH2NhYAL9dPXvyyScRFBRkUd2NNUbUxisjRE3U1atXAcDih+t0Oh02bdoERVHw+OOPo7y83Gx/cXExAMDb27vWsb6+vnWuYF2fmkv4L7/8stm8NqdPnzZ7UNAa7733Hl5//XXs3bsXHTp0sKmOhlRffL/88guWLVuGJ598Evfffz+8vLwQFhaG9evX48KFC0hKSqpVn4eHB4Dfz3VD4VjqYFMdlgoMDARQe5V4rVaL0NBQ5OTkAAC++OILHD16FFOnTrW47sYaI2pzuisjGRkZaodA+H26YZ4P61z/lsWt1PwSsmbio759+2LmzJlYsWIFXn31VYSEhJj2+fr6AkCdfyiKi4sRHBxscTsATA/epaSk2Lw69fVWr16Njz/+GJ999lmdf+TUdqv4albAvu2228y2GwwGtGrVCtnZ2bWOqaioAPD7uW4oHEsNy9vbGx07dsSxY8dq7ausrISPjw8AYOPGjdizZw9cXGpfB1iyZAmWLFmCb775xuyKU2ONEbXxyghRE9W2bVsoioJLly5Zddyrr76KTp064dChQ2bbu3btCm9v71oPBB48eBAVFRXo2bOnVe20b98eOp0Ohw8ftuq4G4kI5syZg6NHjyIrK6vJJSKWxlfzB/iXX34x215aWoqLFy/WukUDwHRu27Vr5+CozXEsNbxx48bh0KFD+O9//2vaVlZWhtOnT5te9920aRNExOwnPz8fwG+3+ESk1q2vxhojamMyQtREeXp6Ijw83PR8jqVqLrHfONeCTqfDrFmzsH37dmzZsgUlJSU4evQoZsyYgcDAQMTFxVndzmOPPYatW7ciNTUVJSUlqKqqwrlz50x/kMePH4927drVO4X4sWPHsHz5cqxfvx4ajabWcgYrVqywKi5L27WUpfGFhYVh8ODBWL9+Pfbt24fy8nKcPXvW1K9PPPFErbprzq2lc1PYimOp4cfSzJkzERoaiilTpuDMmTMoLCzEnDlzUF5eftMHgS3RWGNEdY0+z5qNnHBGuWaN58M2sHIG1vj4eNFoNFJWVmbatn37domIiBAA0qZNG3nmmWfqPHb27Nm1Zs2srq6WpKQk6dixo2g0GvHz85ORI0fK8ePHTWXWrFkjnp6eAkA6duwoOTk5sm7dOjEYDAJAQkND5cSJEyIicu3aNZkzZ46EhISIm5ub+Pv7y6hRoyQ7O1tEfpseG4AsXLjwpp/x6NGjAuCmP0lJSaay+/fvl379+klgYKBpf0BAgERFRcnnn39uKmdJu5bWZ018BQUFkpCQIJGRkeLu7i7e3t7Sr18/ef/99+tsPzo6WoKCgsxmbLWELd8/jqWGHUsiImfPnpUJEyaIn5+fuLu7y7333iu7du2q95j8/PybzsAqYtsYccLfz5wOnmzD82Eba5ORkydPipubm2zevLkBo2o4VVVVMmDAANm4cWOLaNcaBQUFotPpZMWKFVYfa8v3j2PJudoVsX2MOOHvZ04HT9SURUZGIjExEYmJiTdddbSpqqqqQlZWFkpLSxt15Wi12rXWokWL0L17d8THxzdKexxLztNujcYeI2pqscnI8ePH8eyzz+LOO++EXq+Hm5sbfHx8cPvttyM6Ohr79+9XO0ST+pa4vnEJ8JofrVaLtm3bYtCgQUhKSkJRUZEKkZMjzJs3D2PGjMH48eOtfgBRTXv37kVmZiZ27dpl8fwWztyuNZKTk3H48GHs3LkTGo2m0drlWHKOdgH1xohq1L42YylHXnbasGGDaDQa+cMf/iC7d++WoqIiuXr1quTk5Mh7770nUVFR8ve//90hbdnL0iWuIyIixMfHR0R+u5dbVFQk//znP2XKlCmiKIoEBgbKN99847C4nPAyYJMAG1btrfHxxx/LnDlzHBwRNbasrCxZunRprZVlrWHv949jqWmzd4w44e/ndKebZ8ReBw4cQFxcHAYOHIiPP/4Ybm6/d0F4eDjCw8Ph6+uLkydPqhjlb77//nskJiZixowZuHLlisULJSmKAl9fXwwaNAiDBg1CdHQ0xo0bh+joaJw4ccL0zruzKy8vxwMPPICvvvrKqduw1JAhQzBkyBC1wyA7Pfzww3j44YdVjYFjqWlrCmOksbW42zSLFy9GVVUVXnvtNbNE5HoPPfQQnnnmmUaOrDZHLXE9evRoTJkyBXl5eVi7dq0DI1TXxo0ba62Q6oxtEBG1dC0qGamoqMCePXvQunVr3HvvvRYfJw5cKrtz585QFAUuLi7o2bOnaarjF198ET4+PtDpdHjrrbcc9plrTJkyBQCwa9cuh9dtKUv6MT4+HlqtFgEBAaZtTz/9NLy8vKAoimm65YSEBMyaNQs5OTlQFAWRkZFYtWoVdDod2rZti+nTp5tWzoyKijJbK8OeNgBg9+7dMBgMWLJkSYP2FxFRi6HyfSKLOeIe2IkTJwSA9OnTx6rjFi5cKFqtVjZv3izFxcVy5MgR6dGjh7Rp00Zyc3NN5ebPny8AZM+ePXLp0iXJy8uTAQMGiJeXl1RUVIiISGVlpXTo0EFCQkJq3Q98/vnnJSUlpc4Y7rvvPoufGalLSUmJAJD27dtb89FvypbzYWk/xsbGSrt27cyOTUpKEgCSn59v2jZq1CiJiIgwKxcXFydeXl5y7NgxuXr1qmRnZ0vv3r1Fr9fLmTNnHNLGjh07RK/XS2JiolWfX8S+Z0aIajjhMwHUiJxwfLSsV3tLSkoA1L240804eqlsV1dXPPfcczhz5gy2b99uOqasrAyZmZl4/PHH7fyUddPr9VAUxeoFrBzFln60lZubm+nqS5cuXZCamorS0lK7lyKvER0djZKSEixYsMAh9RERtXQtKhmpSUKsWQXS0UtlA8DUqVPh4+ODlStXmrZt2bIFI0aMgMFgsDg2a9Q8ANtQ9d+Kvf1oj169esHT09OupciJiKjhtKhkpEOHDtDpdDhx4oTFxzh6qeyaup588kl89dVX+PrrrwEAb775ZoNObFPzmTt16tRgbdSnIfrRGu7u7qYFqYiIqGlpUcmIu7s7HnroIRQUFODLL7+8abmLFy9i6tSpABy/VHaN+Ph4aDQapKSkYN++fWjfvj0iIiJsqssSu3fvBgAMHTq0wdqoT0P1oyWMRmODt0FERLZrUckI8Nv0uu7u7pg5cybKy8vrLPPDDz+YXvt19FLZNYKDgzF27Fhs27YNCxYsQEJCgk31WCI3NxcpKSkIDg5usGdSbsWafnRzczO7rWWvvXv3QkTQp0+fBmuDiIhs1+KSke7du+Odd97BDz/8gAEDBmDnzp24dOkSjEYjfv75Z6xfvx5PPPGEafpdRy+Vfb1Zs2ahsrISRUVFuP/+++3+bCKCy5cvo7q6GiKC/Px8pKWloV+/fnB1dUVWVpZqz4xY04+RkZG4ePEisrKyYDQakZ+fj9OnT9eqs1WrVrhw4QJOnTqF0tJSU3JRXV2NoqIiVFZW4siRI0hISEBISIjp9WZ729i1axdf7SUiciR13+axnKNfVTpz5oy88MIL0q1bN/H29hZXV1fx9fWVe+65R5544gn58ssvTWUdvVT29QYPHiwbNmyoM0ZLlrj+8MMP5a677hJPT0/RarXi4uIiAERRFPH19ZV7771XEhMTpbCw0GF9J2Lb+bCkH0VECgsLZfDgwaLT6SQsLEyeffZZmT17tgCQyMhI0yu63333nYSGhoqHh4f0799fcnNzJS4uTjQajQQFBYmbm5sYDAYZMWKE5OTkOKyNnTt3il6vl8WLF1vdb+CrveQATvjqJjUiJxwf6YqIhXOMqyw9PR3jxo2zeEp0alhN9XxMnz4dGRkZKCwsVDuUOimKgrS0NIwdO1btUMiJNdXvHzUNTjg+MlrcbRpq/qqqqtQOgYiIrMBkhIiIiFTFZISajZdeegmbNm3CpUuXEBYWhm3btqkdEhERWaDuZWuJnNDSpUuxdOlStcMgIiIr8coIERERqYrJCBEREamKyQgRERGpiskIERERqYrJCBEREanK6d6mURRF7RDoOjwf1hs3bhzGjRundhjUDPD7R82F0yQjUVFRSEtLUzsMIrrO/v37sXLlSn43icguTrM2DRE1PU64BgYRNT1cm4aIiIjUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVMVkhIiIiFTFZISIiIhUxWSEiIiIVOWmdgBE5Bzy8/Px/vvvm2379ttvAQDr1q0z267X6zFhwoRGi42InJsiIqJ2EETU9F27dg1t27bF5cuX4erqCgCo+fWhKIqpnNFoxOTJk/HWW2+pESYROZ8M3qYhIou4u7tj9OjRcHNzg9FohNFoRGVlJSorK03/NhqNAICJEyeqHC0RORMmI0RksYkTJ6KioqLeMr6+vrj//vsbKSIiag6YjBCRxQYPHgx/f/+b7tdoNJg0aRLc3Pg4GhFZjskIEVnMxcUFsbGx0Gg0de43Go18cJWIrMZkhIisMmHCBNOzITe67bbb0Ldv30aOiIicHZMRIrLKvffei9DQ0FrbtVotJk+ebPZmDRGRJZiMEJHVHnnkkVq3aioqKniLhohswmSEiKwWGxtb61ZNZGQkunXrplJEROTMmIwQkdU6deqELl26mG7JaDQaPPbYYypHRUTOiskIEdnk0UcfNc3EWllZyVs0RGQzJiNEZJMJEyagqqoKANCjRw+EhYWpHBEROSsmI0Rkk5CQENx3330AgMmTJ6scDRE5M7unSRwzZowj4iAiJ3Tt2jUoioJPPvkE+/btUzscIlJB3759MXPmTLvqsPvKyLZt23Du3Dl7qyFymAMHDuDAgQNqh+FUzp07h23btll9XHBwMNq1awedTtcAUVFTYev4oObvwIED2L9/v931KFKzBritFSgK0tLSMHbsWLuDIXKEmqt1GRkZKkfiPNLT0zFu3DjY8uvgp59+QmRkZANERU2FPeODmjcH/b7N4DMjRGQXJiJEZC8mI0RERKQqJiNERESkKiYjREREpComI0RERKQqJiNNzIoVK9C2bVsoioK1a9eatu/cuRM+Pj746KOPGjyG6upqpKSkICoqyqLyU6f+P/buPC7Kcv8f/2uAgZkBhkVR+IiQgBsulVpHyY6a5SczULbApbJzjrlUiJqhueTKySXwY0F+LA/1bVFAfWDlUsfj0TLNk5lpdDKkg0i4ICogiwzw/v3hj/k0AjoDAzfL6/l4zOOh11z3fb3v+75m5s29XNdf4OzsDJVKhZMnT1rc3po1a9CnTx9otVo4OjqiT58+WLJkCYqLiy1elzW15D4nIurImIy0Mi+//DKOHDlSp7ylHqnLysrCH//4R8ydOxdlZWVmLfPuu+/inXfeaXSbX331FaZNm4bc3FxcunQJK1euxJo1axAREdHodVoDH2MkImoZTR6BlVrGuHHjUFRU1Kxt/PDDD1ixYgVmzpyJ0tLSFvsxtre3xwsvvGAcOCsyMhLp6elIT0/HhQsX4OXl1SJx3K4l9rm5ysvLMXr06HoTVSKito5nRjooEUF6ejo2b95sLLv33nuxY8cOTJ48GQ4ODhatr3Yq+cbYuXNnnRE8u3XrBgC4ceNGo9fbnmzZsgWXL19WOgwiombRosnIhg0b4OjoCBsbGwwePBhdu3aFWq2Go6MjBg0ahIcffhjdu3eHRqOBq6srXnnlFZPlv/rqKwQGBsLFxQUajQYDBgzA559/DgB477334OTkBJVKBTc3N2RkZOD48ePw9fWFra0tJk2aZFGsGzduhEajQZcuXTBjxgx4eXlBo9EgKCgIx44dM6krIkhISEDfvn3h4OAANzc3TJgwAT///HOj6t3u8OHD8PHxgUqlwltvvQUASE5OhqOjI3Q6HXbt2oWxY8dCr9fD29sbW7duNVm+uroa8fHx6N27N7RaLTp37owePXogPj6+USPnigjWrVuH3r17w8HBAS4uLpg/f77F67mTrKwsuLq6wtfX16rrNVdT9rm5fScmJgb29vbw9PQ0lr3wwgtwdHSESqXClStXAACxsbGYN28esrOzoVKpjIOM7du3D3q9HqtXr26JXUJE1HykiQBIamqq2fVfe+01ASDHjh2T0tJSuXLlijz++OMCQHbv3i0FBQVSWloqMTExAkBOnjxpXDY9PV2WLVsmV69elcLCQhk6dKh06tTJ+P5PP/0kOp1Onn32WWPZwoUL5d13323Utk2fPl0cHR3lp59+koqKCsnMzJQHHnhAnJ2dJTc311hv6dKlYm9vLx988IFcv35dTp06JYMGDZLOnTvLxYsXLa6XlZUlAOTtt982lp0/f14AyJtvvmksW7RokQCQf/zjH1JUVCSXL1+Whx9+WBwdHaWystJYb/Xq1WJrayu7du2SsrIy+e6776Rr164ycuTIBrf9D3/4g9x77731vrdo0SJRqVTyxhtvyLVr16SsrEySkpIEgHz//feW7eTfqayslLy8PHnzzTfFwcFBPvjgg0atJyIiQiIiIhodR62m7HNz+87kyZOla9euJu2uW7dOAEhBQYGxLDw8XPz9/U3qffbZZ+Ls7CwrVqxo8rampqaKFb4OqJ1i/6CGWOn7Nk2xyzSBgYHQ6XTo1KkTJk6cCODWlOSdO3eGTqfDlClTAMDkrEFERARee+01uLm5wd3dHSEhISgsLERBQQEAoG/fvkhMTMT777+Pjz76CFu3bsXNmzfx5z//udFx2tnZGc9kBAYGIjk5GSUlJUhJSQFw61p+QkICwsLCMGXKFLi4uGDAgAHYtGkTrly5YrwMYm69xggKCoJer4eHhweio6NRWlqK3Nxc4/sZGRkYPHgwQkJCoNVqMWjQIIwfPx5ffvklKisrLWqrvLwciYmJePTRRzF37ly4urpCq9XC3d290fHX6t69O7y9vbFs2TKsXbsWUVFRTV5nc7nbPgfu3neaaty4cSguLsaSJUussj4iIqW0intG7O3tAQBVVVXGMrVaDQAwGAwNLldbp7q62lj2/PPPIyIiAjNmzEBaWhrWrl1r1ViHDBkCnU5nTJIyMzNx48YNDBkyxKTeAw88AHt7e+NpeXPrNVXtvvz9fquoqKhzM2p1dTXUajVsbW0tWv/Zs2dRVlaG0aNHNz3Y25w/fx6XL1/Gxx9/jPfffx/3339/m7hPor59Xp/b+w4REd3SKpIRc+3evRsjR46Eh4cHHBwc6txTUmv16tW4ceNGs/2QOTg4GM/GXL9+HQDg5ORUp56rqytKSkosqtccnnjiCXz33XfYtWsXysvLcfz4cWRkZODJJ5+0OBnJy8sDAHh4eFg9TrVaDQ8PD4wZMwbbtm1DZmYm4uPjrd6Okn7fd4iI6JY2k4zk5uYiNDQUnp6eOHbsGIqKirBmzZo69QwGA2bPno2EhAQcPXoUq1atsmocBoMB169fh7e3N4BbiQSAepOJxtRrDsuWLcMjjzyCqVOnQq/XIywsDE899VSjxgapferl5s2b1g7TREBAAGxtbZGZmdms7bSk2/sOERHd0maSkdOnT8NgMGDWrFnw8/ODRqOp93HSl156CdOmTcOcOXMwd+5crFy5EkePHrVaHAcPHoSIYOjQoQCA/v37w8nJCcePHzepd+zYMVRWVmLw4MEW1WsOmZmZyM7ORkFBAQwGA3Jzc5GcnAw3NzeL19W/f3/Y2Njg0KFDVomtsLCw3iedsrKyUF1dje7du1ulndbg9r4D3Lqv5G6Xd4iI2rs2k4z4+PgAAPbv34+KigpkZWXVuc8iKSkJ3bp1Q1hYGAAgPj4egYGBmDx5cqOHFq+pqcG1a9dQVVWFU6dOITY2Fj4+Ppg6dSqAW2cK5s2bh507d+LDDz9EcXExTp8+jZkzZ8LLywvTp0+3qF5zePHFF+Hj42OVMTs8PDwQHh6O7du3Y8uWLSguLsapU6cafQOuo6MjvvjiCxw4cADFxcUwGAz4/vvv8eyzz8LR0RFz585tcsxKuVvfAW6dAbp69SoyMjJgMBhQUFCAc+fO1VmXu7s78vPzkZOTg5KSEhgMBuzdu5eP9hJR+9DU53FgwaO9GzZsEJ1OJwDknnvuka+++kpef/11cXFxEQDStWtX+eijj2Tbtm3StWtXASBubm6ydetWERGJi4sTd3d3cXV1lcjISHnrrbcEgPj7+8t9990nKpVK3N3d5ciRIyIiMmfOHLGxsREA4uLiIsePH7do26ZPny5qtVq6desmdnZ2otfrZcKECZKdnW1Sr6amRtatWyc9e/YUtVotbm5uEhoaKmfOnLG43htvvGHcdkdHRwkLC5M333xTPD09BYDodDoJCQmRpKQk477s2bOnZGdny+bNm0Wv1wsA8fX1lV9++UVERA4cOCCdOnUSAMaXWq2Wvn37yo4dO4xtHz16VB566CHx8vIy1vP09JSgoCA5dOiQsV5JSYn85S9/kU6dOomTk5MMHz5cli5dKgDE29tbfvjhB4v2c0hIiPTo0UOcnJzEwcFB/P39JTo6Wk6fPm3RempZ41Gzpu5zc/tOYWGhjBo1SjQajfTo0UNeeuklmT9/vgCQgIAA42PAJ06cEF9fX9FqtTJ8+HC5ePGi7NmzR5ydnWXVqlVN2lYRPrpJd8b+QQ2x1qO9KpGmjfmtUqmQmpraqMGzWrsZM2YgPT0dhYWFSofSJMnJycjKykJiYqKxrLKyEgsWLEBycjKuXbsGrVarYITWFRkZCQBIT09XLIa21nfS0tIQFRXF+XioXuwf1BArfd+mc26au/j9Y8Nt0cWLFxETE1NnNl17e3v4+PjAYDDAYDC0q2SktWjrfYeIqKW0mXtGrOHnn3+GSqW66ys6OlrpUK1Gq9VCrVZjy5YtuHTpEgwGA/Lz8/Huu+9i6dKliI6Ohl6vt2qbHXE/ExFR43WoZKRPnz4Qkbu+tm3bhldffRUpKSkoKipCjx49sH37dqXDbxQXFxd88cUX+PHHH9GrVy9otVoEBgYiJSUFr7/+Ot5//32rt2nJfm6P2kvfscT+/fuxcOFC7NixA35+fsaE8+mnn65Td8yYMXB2doatrS369euHEydOKBCx+VasWIHAwEDo9Xo4ODggICAAr7zySoM3hNfU1CAxMRFBQUFNbttgMCA+Ph4BAQGwt7eHq6sr+vfvj5ycnAaXqaioQJ8+fbB48WJj2SeffII1a9YodrauPfePWuYcd/aNO2jqXSewcG4aouZmrblpOpKm3KC4dOlSCQ4OluLiYmOZv7+/8abpzz77rM4ye/fulfHjxzc63pY0YsQISUpKksLCQikuLpbU1FRRq9Xy+OOP16n7yy+/yEMPPSQAGpzbyRKhoaHSu3dv+eabb8RgMEh+fr6EhITc8ebuuXPnCgBZtGiRSfmGDRtkxIgRcu3aNYvjYP+4M3OOe3vtG21+bhoiavtef/11bNu2DWlpaXB2djZ5b+PP4i8nAAAgAElEQVTGjbCxscH06dNRVFSkUIRN5+TkhOnTp8Pd3R3Ozs546qmnEBoain379uH8+fPGej/88AMWLFiAmTNn4r777mtyu9u2bUNGRgbS09Pxhz/8AXZ2dvDy8sKuXbvQv3//epc5cuQIfvzxx3rfmz17Nu6991488cQTJlNvNKeO0D/MOe7sG3fHZISIGuXs2bNYsmQJli9fbhyZ9/eCgoIQGxuL3377DS+//LICEVrHZ599VmfahM6dOwMAysrKjGX33nsvduzYgcmTJ8PBwaHJ7b799tsYNGgQBgwYYFb98vJyzJ8/Hxs2bGiwzrJly3Dy5Mk71rGWjtI/zDnu7Bt3x2SEiBpl48aNEBGEhIQ0WGfVqlXo1asX3n33Xezfv/+O6xMRJCQkGGc6dnNzw4QJE0wmFkxOToajoyN0Oh127dqFsWPHQq/Xw9vbG1u3bjVZX3V1NZYuXQofHx9otVoMHDgQqampTdvo/99vv/0GrVaLHj16WGV9t6usrMQ333xj0V/RixYtwgsvvHDHeaPc3NwwYsQIbNiwodkf0+3I/aM5tYe+UR8mI0TUKLt370bv3r2h0+karKPVavHee+/BxsYG06ZNQ2lpaYN1ly1bhoULF2LRokW4fPkyvvzyS5w/fx4PP/wwLl26BACYNWsW5syZg/Lycjg7OyM1NRXZ2dnw8/PDtGnTTIbWX7BgAdauXYvExERcuHABwcHBmDRpUp0pGSxVVlaGAwcOYNq0acYZm60tPz8flZWV+O677zBq1Ch4eXlBo9Ggb9++SEpKqvNj8fXXXyM7O7veqRVud//99+O3337DDz/80Cyx1+qo/aO5tYe+UR8mI0RksdLSUvznP/+Bv7//XesOGzYMc+bMQU5ODhYsWFBvnfLyciQkJCAsLAxTpkyBi4sLBgwYgE2bNuHKlSv1TjcQFBQEvV4PDw8PREdHo7S0FLm5uQBuPTWQnJyM0NBQhIeHw9XVFYsXL4ZarUZKSkqTtj0+Ph5eXl5Wn4Tz92qf1PHw8MDq1auRmZmJS5cuYcKECXjxxRfx8ccfG+uWl5cjNjYWycnJZq27Z8+eAG7N99VcOnL/aG5tvW80xCrJSFRUlFnjSvDFV0u8tm/fju3btyseR1t6RUVFWfSZv3z5MkTkjn/1/t6qVavQu3dvJCUl4fDhw3Xez8zMxI0bNzBkyBCT8gceeAD29vZ15qG6Xe0Zitq/fM+cOYOysjKTm/m0Wi08PT1NTutbaufOnUhLS8Pnn39e54ZMa6q9r6Bfv34ICgqCu7s7XFxcsHz5cri4uJj8+L766qt4/vnn0a1bN7PWXXvMas8mNIeO2j9aQlvvGw2xygissbGxGDZsmDVWRdRktcPez5kzR+FI2o6jR49adONaRUUFAJh9M55Go0FKSgqGDx+OP/3pT1izZo3J+9evXwdw68mV27m6uqKkpMTs2AAYT/cvXrzYZEwFAPDy8rJoXbW2bduGhIQEHDx4EP/1X//VqHWYqzbGK1eumJTb29vD19cX2dnZAIDDhw/j9OnTSEhIMHvdtaMt1x7D5tAR+0dLaet9oyFWSUaGDRvWLuemobapdo4E9knLWJKM1H5pWTJQ0rBhwzB37lysX78eK1euNM7EDdz6QQFQ74/K9evX4e3tbXY7AIw36iUmJiI2NtaiZevz5ptv4vPPP8eBAwfq/UG0NicnJ/Ts2RM//fRTnfeqqqrg4uICANiyZQv+8Y9/wMam7knu1atXY/Xq1fj2229NzihUVlYCQLNOAdHR+kdLaut9oyG8Z4SILNalSxeoVCqLx4dYuXIl+vTpg++//96kvH///nBycqpz8+CxY8dQWVmJwYMHW9RO9+7dodFo6szJZCkRQVxcHE6fPo2MjIwWSURqRUVF4fvvv8evv/5qLCsrK8O5c+eMj3SmpKTUGdm4oKAAwK0nKESkzqWN2mPWtWvXZou9o/QPpbTlvtEQJiNEZDGdTgc/Pz/k5eVZtFzt6fjbx+3QaDSYN28edu7ciQ8//BDFxcU4ffo0Zs6cCS8vL0yfPt3idp577jls3boVycnJKC4uRnV1NfLy8nDhwgUAQHR0NLp27XrH4cZ/+uknrF27Fu+88w7UanWde23Wr19vUVzmtgsAc+fOha+vL6ZOnYrc3FwUFhYiLi4O5eXlDd7oaY7aY2buGBWN0VH6h7V1hL7RoKaO4QoOB0+tDIeDt1xjhvuOiYkRtVotZWVlxrKdO3eKv7+/AJDOnTvLiy++WO+y8+fPrzPcd01Njaxbt0569uwparVa3NzcJDQ0VM6cOWOsk5SUJDqdTgBIz549JTs7WzZv3ix6vV4AiK+vr/zyyy8iInLz5k2Ji4sTHx8fsbOzEw8PDwkPD5fMzEwRuTWcNgBZunRpg9t4+vRpAdDga926dca6R48elYceeki8vLyM73t6ekpQUJAcOnTIWM+cdmudP39eJk6cKG5ubuLg4CAPPvig7N27947LFBQU1Dvkd61x48ZJt27dpKam5q7t12L/aJg5x7099w1rDQfPZITaHSYjlmvMj01WVpbY2dnJBx980ExRNa/q6mp5+OGHZcuWLR2iXRGRK1euiEajkfXr11u0HPtH+22zVmP7BuemISJFBQQEYMWKFVixYkWDM9i2VtXV1cjIyEBJSQmio6Pbfbu1li1bhvvuuw8xMTHN3hb7R+tv8/dasm/Up1UnI7dPN71kyZI71k9ISIBKpYKNjQ369OmDL7/8stliUalUUKvV6NatGyZPnox///vfVmvrduvXrzfeELZp0yZj+Z49e+Di4oJPP/202dqudaepr+vbNyqVCvb29ujSpQtGjhyJdevW4dq1a80eJ7WshQsXIjIyEtHR0W1qsrODBw9ix44d2Lt3r9ljYbTldoFb348nT57Enj17oFarW6RN9o/W3WYtJfpGHU09t4IWuExTe43R09NTKisr661TVVUlvr6+AkBGjx7drLG4uLiIiMiNGzfkk08+ER8fH3FycpKff/652drNysoSAPL2228byz777DPR6/XyySefNFu7IuZPff37fVNTUyPXrl2Tf/7znzJ16lRRqVTi5eUl3377bbPGKsLLNI3RlCniRUQ+//xziYuLs2JEZE0ZGRkSHx8vVVVVjVqe/aP9amrf6HCXaQYPHoyLFy8iIyOj3vd37Nhh9ihz1uLo6Ijg4GD8z//8D27cuIE333yzRdsfN24cioqKEBwc3GxtNHbqa5VKBVdXV4wcORIpKSlIS0vDpUuXjDG3d+Xl5fWeRWprbZhrzJgxeP3115UOgxowfvx4LFy4sM5TKi2F/aP1Urpv1GozycisWbMA3Jo6uT4JCQmYN29eS4Zk9OCDDwIAfvzxR0XatxYRQXp6uslwwtaa+joiIgJTp07F5cuXTS41tVdbtmzB5cuX23wbREQtoc0kI4888gj69u2Lf/7znzhz5ozJe19//TXKysowZsyYepf96quvEBgYCBcXF2g0GgwYMACff/45AOC9996Dk5MTVCoV3NzckJGRgePHj8PX1xe2trZmzXRYVVUFwHToYzFjumtL6t3u8OHD8PHxgUqlwltvvQXA8umz4+Pj0bt3b2i1WnTu3Bk9evRAfHx8s41cOnXqVADA3r17m2X9TWHOcYiJiYG9vT08PT2NZS+88AIcHR2hUqmMwzPHxsZi3rx5yM7OhkqlQkBAADZu3AiNRoMuXbpgxowZxpk2g4KCTObVaEobALBv3z7o9XqsXr26WfcXEZE1tZlkBABmzJgBAHX+sn7jjTcwd+7cBpe7dOkSoqKikJOTg/z8fDg5OWHy5MkAbv1Afvvtt9DpdBg/fjwmTJiAIUOGYPLkydi8ebPJDIgNqb1R9t577zWWmTPdtSX1bjd8+HAcOXLEpMyS6bPXrFmDpUuXYt26dbh69Sq++OILVFRUwNXV1Tj0srXVXub5/aiBrYU5x2Hjxo11ErWkpCQsX77cpGzDhg0IDg6Gv78/RARnz55FTEwMpk6dirKyMsyePRs5OTk4ceIEqqqq8Nhjj+H8+fNNbgP4v+G3a2pqrLdziIiaWZtKRp599lk4Ojri/fffR3l5OYBbP2zffvvtHc9gRERE4LXXXoObmxvc3d0REhKCwsJC49C4ffv2RWJiIt5//3189NFH2Lp1K27evIk///nPd4yntLQUO3bswMsvv4wuXbpg9uzZAMyf7rox02Kb607TZwNARkYGBg8ejJCQEGi1WgwaNAjjx4/Hl19+aZyfwNqcnZ2hUqksntSquTXncbidnZ2d8exLYGAgkpOTUVJSYrVpy8eNG4fi4uK7PnlGRNSatKlkxMXFBZMmTcK1a9ewbds2ALcmOpo1a5Zximhz1D669PtJnJ5//nlERERgxowZSEtLw9q1axtcvqioCCqVCi4uLpg9ezaeeOIJ/Otf/zLeQGvudNdNnRbbXLdPnw3cmpVRREzqVVdXQ61WN9uNTKWlpRAR6PX6Zll/Y7XUcajPkCFDoNPpWv205UREzalNJSPA/93IumnTJly/fh3p6enGyzcN2b17N0aOHAkPDw84ODjglVdeqbfe6tWrcePGjbveFOji4gIRQVVVFfLy8vC3v/0Nvr6+xvfNne7a2tNiW+KJJ57Ad999h127dqG8vBzHjx9HRkYGnnzyyWZLRn755RcAQJ8+fZpl/Y2l5HEAbt1rVHuWjoioI2pzych9992HoUOH4l//+hemT5+OyMhIuLm5NVg/NzcXoaGh8PT0xLFjx1BUVIQ1a9bUqWcwGDB79mwkJCTg6NGjWLVqVaNjNHe6a2tPi22JZcuW4ZFHHsHUqVOh1+sRFhaGp556Cu+8806ztblv3z4AwNixY5utjcZQ8jgYDIZmb4OIqLWzUzqAxpg1axa++eYbbN++HVlZWXese/r0aRgMBsyaNQt+fn4Abo2BcbuXXnoJ06ZNQ1hYGH777TesXLkSY8aMwbBhwyyOz9zprq09LbYlMjMzkZ2djYKCAtjZNX83uHjxIhITE+Ht7Y0//elPzd6eJSw5DnZ2diaXu5rq4MGDEBEMHTq02dogImrt2tyZEQB46qmn0LlzZ4SGhhoTjIb4+PgAAPbv34+KigpkZWXVuQcgKSkJ3bp1Q1hYGAAgPj4egYGBmDx5MoqLiy2Oz9zprq09LbYlXnzxRfj4+Fh9zggRwY0bN1BTUwMRQUFBAVJTU/HQQw/B1tYWGRkZre6eEUuOQ0BAAK5evYqMjAwYDAYUFBTg3Llzddbp7u6O/Px85OTkoKSkxJhc1NTU4Nq1a6iqqsKpU6cQGxsLHx8f42PPTW1j7969fLSXiNqepo7himYcDv5O002/8sorcuTIEeP/Fy9eLJ6engJAbGxsJDAwUL766isREYmLixN3d3dxdXWVyMhIeeuttwSA+Pv7y3333ScqlUrc3d2N65szZ47Y2NgIAHFxcZHjx4/L119/Lb169TJO/+zl5SWRkZENxm7OdNfm1nvjjTeka9euAkAcHR0lLCxM3nzzTeP26nQ6CQkJsWj67AMHDkinTp1MpkNXq9XSt29f2bFjh7Ftc6a+/uSTT2TgwIGi0+nE3t7euO9UKpW4urrKgw8+KCtWrJDCwsLGdgWLNGZ4YnOPV2FhoYwaNUo0Go306NFDXnrpJZk/f74AkICAAMnNzRURkRMnToivr69otVoZPny4XLx4UaZPny5qtVq6desmdnZ2otfrZcKECZKdnW21Nvbs2SPOzs6yatUqi7a/qcN9U/vG/kENsdZw8CqR2x6psJBKpUJqamqzDZRFzSM5ORlZWVlITEw0llVWVmLBggVITk7GtWvXoNVqFYyw8SIjIwEA6enpCkdiasaMGUhPT0dhYaHSodSRlpaGqKioOk9YEQHsH9QwK33fprfJe0aoaS5evIiYmBicPHnSpNze3h4+Pj4wGAwwGAxtNhlpzX7/ODkREd3SJu8ZoabRarVQq9XYsmULLl26BIPBgPz8fLz77rtYunQpoqOjW919HURE1H4xGemAXFxc8MUXX+DHH39Er169oNVqERgYiJSUFLz++ut4//33lQ6x3Xn11VeRkpKCoqIi9OjRA9u3b1c6JCKiVoOXaTqohx9+GH//+9+VDqPDiI+PR3x8vNJhEBG1SjwzQkRERIpiMkJERESKYjJCREREimIyQkRERIqyyg2sR48etcZqiKwiLy8PwK2Bmsg8tZ9h7jOqD/sHNSQvL88qE31aZQRWIiIi6pgiIiKUH4GVwwMTdVwcJpyIrIH3jBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaKYjBAREZGimIwQERGRopiMEBERkaLslA6AiNqGvLw8PPvss6iurjaWXbt2Dc7Ozhg5cqRJ3d69e+N///d/WzhCImqrmIwQkVm8vb1x7tw5ZGdn13nv0KFDJv//4x//2FJhEVE7wMs0RGS2Z555Bmq1+q71oqOjWyAaImovmIwQkdkmT56MqqqqO9bp168fAgMDWygiImoPmIwQkdn8/f0xcOBAqFSqet9Xq9V49tlnWzgqImrrmIwQkUWeeeYZ2Nra1vteVVUVIiMjWzgiImrrmIwQkUUmTpyImpqaOuU2NjYYOnQo7rnnnpYPiojaNCYjRGQRLy8vPPTQQ7CxMf36sLGxwTPPPKNQVETUljEZISKLPf3003XKRARhYWEKRENEbR2TESKyWEREhMl9I7a2tnj00UfRpUsXBaMioraKyQgRWczNzQ2PPfaYMSEREUyZMkXhqIiorWIyQkSNMmXKFOONrGq1GhMmTFA4IiJqq5iMEFGjhISEwMHBAQAQHBwMJycnhSMioraKyQgRNYqjo6PxbAgv0RBRU6hERJQOorWKjIzE9u3blQ6DiIjauNTUVDz11FNKh9FapXPW3rsYOnQo5syZo3QYrV5UVBRiY2MxbNgwpUNpMxITEwGgTfev6upqpKamYtKkSUqH0q7w89S+REVFKR1Cq8czI3dQO6x1enq6wpG0fiqVipm/hdpL/6qoqIBGo1E6jHaFn6f2hcfzrtJ5zwgRNQkTESJqKiYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI83o5s2bmD17Njw9PaHT6YwTialUKmzatEnp8FqlPXv2wMXFBZ9++qnSoRARUQvhOCPN6I033sC+ffvw888/Iy0tDe7u7rjvvvvQs2dPpUNrtfikORFRx8MzI80oIyMDQ4YMgaurK55//nlEREQ0aj3l5eUICgq6a1l7MG7cOBQVFSE4OFjpUNrtPiYiam2YjDSjvLw8qNXqJq9ny5YtuHz58l3LyLq4j4mIWgaTkWbw97//HQEBAbhw4QLef/99qFSqO85o+tVXXyEwMBAuLi7QaDQYMGAAPv/8cwBAbGws5s2bh+zsbKhUKgQEBNRbBtwamnvp0qXw8fGBVqvFwIEDkZqaCgBITk6Go6MjdDoddu3ahbFjx0Kv18Pb2xtbt25t/p1ihsOHD8PHxwcqlQpvvfUWAPPj3rhxIzQaDbp06YIZM2bAy8sLGo0GQUFBOHbsmLFeTEwM7O3t4enpaSx74YUX4OjoCJVKhStXrgCof78DwL59+6DX67F69eqW2CVERB0Ck5Fm8Nhjj+Hs2bPo2rUrnn32WYgIbty40WD9S5cuISoqCjk5OcjPz4eTkxMmT54MANiwYQOCg4Ph7+8PEcHZs2frLQOABQsWYO3atUhMTMSFCxcQHByMSZMm4fjx45g1axbmzJmD8vJyODs7IzU1FdnZ2fDz88O0adNgMBhaZN/cyfDhw3HkyBGTMnPjjomJwdSpU1FWVobZs2cjJycHJ06cQFVVFR577DGcP38ewK2k5fYhmZOSkrB8+XKTsob2cXV1NQCgpqamWfYBEVFHxGSkFYiIiMBrr70GNzc3uLu7IyQkBIWFhSgoKDB7HRUVFUhOTkZoaCjCw8Ph6uqKxYsXQ61WIyUlxaRuUFAQ9Ho9PDw8EB0djdLSUuTm5lp7s6zOnLjt7OzQt29fODg4IDAwEMnJySgpKamzDxpr3LhxKC4uxpIlS6yyPiIiYjLSKtXeZ1L7V7g5zpw5g7KyMvTv399YptVq4enpiZ9//rnB5ezt7QGgVZwZsYS5cQ8ZMgQ6ne6O+4CIiJTFZKQV2L17N0aOHAkPDw84ODjglVdesXgdpaWlAIDFixdDpVIZX+fOnUNZWZm1Q25THBwcLDrLRERELYvJiMJyc3MRGhoKT09PHDt2DEVFRVizZo3F6/Hw8AAAJCYmQkRMXkePHrV22G2GwWDA9evX4e3trXQoRETUAA56prDTp0/DYDBg1qxZ8PPzAwCoVCqL19O9e3doNBqcPHnS2iG2aQcPHoSIYOjQocYyOzu7NndZioioPeOZEYX5+PgAAPbv34+KigpkZWWZPIoKAO7u7sjPz0dOTg5KSkpgMBjqlNna2uK5557D1q1bkZycjOLiYlRXVyMvLw8XLlxQYtMUUVNTg2vXrqGqqgqnTp1CbGwsfHx8MHXqVGOdgIAAXL16FRkZGTAYDCgoKMC5c+fqrKu+/b53714+2ktEZG1CDYqIiJCIiAiLl8vJyZH7779fAIidnZ0MGjRItm/fLm+88YZ07dpVAIijo6OEhYWJiEhcXJy4u7uLq6urREZGyltvvSUAxN/fX3Jzc+XEiRPi6+srWq1Whg8fLhcvXqy37ObNmxIXFyc+Pj5iZ2cnHh4eEh4eLpmZmZKUlCQ6nU4ASM+ePSU7O1s2b94ser1eAIivr6/88ssvjd5XACQ1NbXRy4uIvPnmm+Lp6SkARKfTSUhIiEVxT58+XdRqtXTr1k3s7OxEr9fLhAkTJDs726SdwsJCGTVqlGg0GunRo4e89NJLMn/+fAEgAQEBkpubKyJS7z7es2ePODs7y6pVq5q0rSKN71/U/lnj80StB4/nXaWpRDgZSEMiIyMBAOnp6QpH0vqpVCqkpqbWGcOjJc2YMQPp6ekoLCxULAZLsH9RQ1rD54msh8fzrtJ5mYbaFUsehyYiotaByQhRG7V//34sXLgQO3bsgJ+fn/Fx7qeffrpO3TFjxsDZ2Rm2trbo168fTpw4oUDElqupqUFiYuIdJyw0p465DAYD4uPjERAQAHt7e7i6uqJ///7IyclpcJmKigr06dMHixcvNpZ98sknWLNmjSLJcXvuFyNHjjQZuuD3r9un3Dh8+DAeeugh6HQ6eHl5IS4uDjdv3rzj+lvbsexImIxQu/Dqq68iJSUFRUVF6NGjB7Zv3650SM3qtddew8aNG/Hqq68iPDwcv/76K/z9/dGpUyd8+OGH2L17t0n9L774Aunp6QgODkZmZiYGDRqkUOTmy8rKwh//+EfMnTu3wbFyzKljiaioKPy///f/8NFHH6GsrAz//ve/4e/vf8fpHBYtWoQzZ86YlIWEhECj0WD06NG4fv16k+MyV0foFw0ZPny48d+ZmZkYM2YMRo8ejYKCAuzcuRN/+9vfMHPmzDuuozUdy46GyQi1C/Hx8bh58yZEBP/5z38QERGhdEjN5vXXX8e2bduQlpYGZ2dnk/c2btwIGxsbTJ8+HUVFRQpF2HQ//PADFixYgJkzZ+K+++5rdB1LbNu2DRkZGUhPT8cf/vAH2NnZwcvLC7t27TIZ2fj3jhw5gh9//LHe92bPno17770XTzzxBKqqqpoc3910hH6h0WhQXFxcZyyl6dOnmwwWuXLlSnh6emL58uVwdHTEsGHDEBcXh/fee6/B0Zhb07HsiJiMELUhZ8+exZIlS7B8+XJoNJo67wcFBSE2Nha//fYbXn75ZQUitI57770XO3bswOTJk+Hg4NDoOpZ4++23MWjQIAwYMMCs+uXl5Zg/fz42bNjQYJ1ly5bh5MmTd6xjDR2lX+zbt69OonX+/Hn8+OOPeOSRRwAAVVVV2L17N0aMGGEyZtPYsWMhIti1a1ed9bamY9lRMRkhakM2btwIEUFISEiDdVatWoVevXrh3Xffxf79+++4PhFBQkKCcXJBNzc3TJgwweSvx+TkZDg6OkKn02HXrl0YO3Ys9Ho9vL29sXXrVpP1VVdXY+nSpfDx8YFWq8XAgQORmpratI1uAZWVlfjmm28sOsOyaNEivPDCC8bRj+vj5uaGESNGYMOGDWjOBxc7cr94/fXXMXv2bOP/f/31V9y4ccM4hlMtf39/AMCpU6fqrKM1HcuOiskIURuye/du9O7dGzqdrsE6Wq0W7733HmxsbDBt2jTjvEX1WbZsGRYuXIhFixbh8uXL+PLLL3H+/Hk8/PDDuHTpEgBg1qxZmDNnDsrLy+Hs7IzU1FRkZ2fDz88P06ZNMxnNdsGCBVi7di0SExNx4cIFBAcHY9KkSTh+/Lj1dkIzyM/PR2VlJb777juMGjUKXl5e0Gg06Nu3L5KSkur8+Hz99dfIzs7GpEmT7rru+++/H7/99ht++OGH5gq/w/aL3377DQcPHkR4eLix7OLFiwBQ5wyKRqOBVqs1xl+rtR3LjorJCFEbUVpaiv/85z/Gv/DuZNiwYZgzZw5ycnKwYMGCeuuUl5cjISEBYWFhmDJlClxcXDBgwABs2rQJV65cwebNm+ssExQUBL1eDw8PD0RHR6O0tBS5ubkAbj2JkJycjNDQUISHh8PV1RWLFy+GWq1GSkpK0za+mdXeoOrh4YHVq1cjMzMTly5dwoQJE/Diiy/i40M55Y0AACAASURBVI8/NtYtLy9HbGwskpOTzVp3z549Adya+qE5dOR+8frrr+Oll16Cjc3//ZTVPjFja2tbp75arUZ5ebnJtramY9mRcW6au8jLy0NaWprSYbQJHXlCvsbIy8uzaAK/y5cvQ0Tu+Nfv761atQqfffYZkpKSEBUVVef9zMxM3LhxA0OGDDEpf+CBB2Bvb19nWoLb2dvbA4DxL+AzZ86grKzM5GZPrVYLT0/PBm8abC1q7znp16+fySPCy5cvx9tvv43Nmzdj8uTJAG49ufX888+jW7duZq279njd/he5tXTUfpGfn49PPvkE69atMymvvWemvhtNKysrodVqjf9vbceyI2MychfffPNNvR9YqmvDhg28uctCljz1U1FRAQBm36yp0WiQkpKC4cOH409/+lOd2aBrH1O8fXwGAHB1dUVJSYnZsQEwnvZfvHixyTgNAODl5WXRulpabXxXrlwxKbe3t4evry+ys7MB3Bq74vTp00hISDB73bU/frXHz9o6ar9Ys2YNpk2bVueGXU9PTwBAcXGxSXlZWRkqKiqMbbbGY9mR8TLNXURERNR5jIyvui8ASE1NVTyOtvSy9PHj2i9CSwZfGjZsGObOnYusrCysXLnS5D1XV1cAqPfH5fr16xadtQFgvPkvMTGxzra29rNmTk5O6NmzJ3766ac671VVVcHFxQUAsGXLFvzjH/+AjY2NcbCt2u1evXo1VCpVnfsgKisrAcDkL3Jr6oj94uLFi/j4448xa9asOu/16NEDzs7OdSa/PHv2LABg4MCBAFrnsezImIwQtRFdunSBSqWyeJyIlStXok+fPvj+++9Nyvv37w8nJ6c6X7jHjh1DZWUlBg8ebFE73bt3h0ajwcmTJy1arrWIiorC999/j19//dVYVlZWhnPnzhkf901JSanzg1pQUADg1hMZIlLn8kbt8eratWuzxN0R+8WaNWswZcoUuLu713nPzs4OTzzxBL788kvU1NQYy/fu3QuVSmV84qg1HsuOjMkIURuh0+ng5+eHvLw8i5arPS1/+w19Go0G8+bNw86dO/Hhhx+iuLgYp0+fxsyZM+Hl5YXp06db3M5zzz2HrVu3Ijk5GcXFxaiurkZeXh4uXLgAAIiOjkbXrl1bdNhxc9ucO3cufH19MXXqVOTm5qKwsBBxcXEoLy9v8GZPc9QeL3PHL7FUR+sXly5dwt/+9jfMmTOnwTpLlizBpUuX8Nprr6G0tBRHjx7FunXrMHXqVPTu3dui+H+vuY9lhybUIE7xbj5wimyLNaZ/xcTEiFqtlrKyMmPZzp07xd/fXwBI586d5cUXX6x32fnz58v48eNNympqamTdunXSs2dPUavV4ubmJqGhoXLmzBljnaSkJNHpdAJAevbsKdnZ2bJ582bR6/UCQHx9feWXX34REZGbN29KXFyc+Pj4iJ2dnXh4eEh4eLhkZmaKiEhoaKgAkKVLl95xO48ePSoPPfSQeHl5CQABIJ6enhIUFCSHDh0yu44lbYqInD9/XiZOnChubm7i4OAgDz74oOzdu/eOyxQUFAgAWbRoUb3vjxs3Trp16yY1NTV3bb+WpZ+njtIvRETmzp0rU6ZMuWu9Q4cOyYMPPigODg7i5eUl8+fPl4qKijsu0xzHUoTfj2ZIYzJyB0xGzMcPm+Ua07+ysrLEzs5OPvjgg2aKqnlVV1fLww8/LFu2bGnXbda6cuWKaDQaWb9+vUXLWfp5Yr9ofo09liL8fjRDGi/TELUhAQEBWLFiBVasWHHHydtao+rqamRkZKCkpATR0dHtts3fW7ZsGe677z7ExMQ0azvsF82vpY5lR8VkhKiNWbhwISIjIxEdHd2mJj07ePAgduzYgb1795o9JkZbbLNWQkICTp48iT179kCtVjd7e+wXzaelj2VHxGTEinbs2AE/Pz/jY2L1ve655x4AwPr16413wW/atEnZwKnNWb16NWJiYvDXv/5V6VDMNnr0aHz00UfGcSDaa5sAsGvXLty8eRMHDx6Em5tbi7XLfmF9Sh3LjoaDnllReHg4wsPDERAQgCtXrhgHD6qurkZlZSVKSkowcuRIAMDLL7+MCRMmGIcXJrLUmDFjMGbMGKXDoHqMHz8e48ePV6Rt9gvrUvJYdiQ8M9ICbG1todVq0aVLF/Tq1atJ6yovLzcZrrqhso6mJfYB9zMRUfNgMtLCMjIymrT8li1bcPny5buWdTQtsQ+4n4mImgeTkVbmq6++QmBgIFxcXKDRaDBgwAB8/vnnAIDY2FjMmzcP2dnZUKlUCAgIqLcMuHVpaOnSpfDx8YFWq8XAgQORmpoKAEhOToajoyN0Oh127dqFsWPHQq/Xw9vbG1u3bm2R7RQRJCQkoG/fvnBwcICbmxsmTJhgMnFWTEwM7O3tTa4lv/DCC3B0dIRKpTLOI1LfPti4cSM0Gg26dOmCGTNmGKeEDwoKMpnoqyltAMC+ffug1+uxevXqZt1fRETtGZORFnLgwAGsX7/+rvUuXbqEqKgo5OTkID8/H05OTsbZQjds2IDg4GD4+/tDRHD27Nl6ywBgwYIFWLt2LRITE3HhwgUEBwdj0qRJOH78OGbNmoU5c+agvLwczs7OSE1NRXZ2Nvz8/DBt2jTjbJvNadmyZVi4cCEWLVqEy5cv48svv8T58+fx8MMPG2fE3LhxI5566imT5ZKSkrB8+XKTsvr2QUxMDKZOnYqysjLMnj0bOTk5OHHiBKqqqvDYY4/h/PnzTW4D+L/5QH4/7DQREVmGyUgzKSoqMnmKZvTo0WYtFxERgddeew1ubm5wd3dHSEgICgsLjXMmmKOiogLJyckIDQ1FeHg4XF1dsXjxYqjVaqSkpJjUDQoKgl6vh4eHB6Kjo1FaWorc3FyLttVS5eXlSEhIQFhYGKZMmQIXFxcMGDAAmzZtwpUrV7B582artWVnZ2c8+xIYGIjk5GSUlJTU2Q+NNW7cOBQXF2PJkiVWWR8RUUfEZKSZuLi4mEzA9M9//rNR66l9pt2SGTnPnDmDsrIy9O/f31im1Wrh6elpchnkdvb29gDQ7GdGMjMzcePGjTqTUD3wwAOwt7c3uYxibUOGDIFOp7vjfiAiopbFZKSFjBw5Ei+//PJd6+3evRsjR46Eh4cHHBwc8Morr1jcVmlpKQBg8eLFJmdnzp07h7KyMovXZ221jzw7OTnVec/V1bXeqcutycHBwaIzTURE1LyYjLQiubm5CA0NhaenJ44dO4aioiKsWbPG4vV4eHgAABITE+tMkX306FFrh20xV1dXAKg36bh+/Tq8vb2brW2DwdDsbRARkWU46Fkrcvr0aRgMBsyaNQt+fn4AAJVKZfF6unfvDo1Gg5MnT1o7RKvo378/nJyccPz4cZPyY8eOobKyEoMHDzaW2dnZWfWy0cGDByEiGDp0aLO1QUREluGZkVbEx8cHALB//35UVFQgKyurzv0T7u7uyM/PR05ODkpKSmAwGOqU2dra4rnnnsPWrVuRnJyM4uJiVFdXIy8vDxcuXFBi00xoNBrMmzcPO3fuxIcffoji4mKcPn0aM2fOhJeXF6ZPn26sGxAQgKtXryIjIwMGgwEFBQU4d+5cnXXWt1+AW0+5XLt2DVVVVTh16hRiY2Ph4+ODqVOnWqWNvXv38tFeIqKmUmSy4DbC0inev/76a+nVq5cAEADi6ekpo0ePrrfuG2+8IV27dhUA4ujoKGFhYSIiEhcXJ+7u7uLq6iqRkZHy1ltvCQDx9/eX3NxcOXHihPj6+opWq5Xhw4fLxYsX6y27efOmxMXFiY+Pj9jZ2YmHh4eEh4dLZmamJCUliU6nEwDSs2dPyc7Ols2bN4terxcA4uvrK7/88otF+woWTpFdU1Mj69atk549e4parRY3NzcJDQ2VM2fOmNQrLCyUUaNGiUajkR49eshLL70k8+fPFwASEBAgubm5IiL17oPp06eLWq2Wbt26iZ2dnej1epkwYYJkZ2dbrY09e/aIs7OzrFq1yqL9JWJ5/6KOw9LPE7VuPJ53laYSEVEoD2r1IiMjAQDp6ekKR9L6qVQqpKam1hmzQ0kzZsxAeno6CgsLlQ6lXuxf1JDW+HmixuPxvKt0Xqahds2SR6KJiEgZTEaIiIhIUUxGqF169dVXkZKSgqKiIvTo0QPbt29XOiQiImoAH+2ldik+Ph7x8fFKh0FERGbgmREiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFG9gvYtvvvnGODgV3VliYiIH8LLAN998AwDsX1Qvfp6oI+EIrHeQkJDQKma5JWqtLl68iO+//x5jx45VOhSiVm3u3LkYNmyY0mG0VulMRoio0dLS0hAVFQV+jRBRE3A4eCIiIlIWkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSFJMRIiIiUhSTESIiIlIUkxEiIiJSlJ3SARBR22AwGHDjxg2TstLSUgDAtWvXTMpVKhVcXV1bLDYiatuYjBCRWa5evYpu3bqhurq6znvu7u4m/x81ahQOHDjQUqERURvHyzREZJauXbvij3/8I2xs7vy1oVKpMHHixBaKiojaAyYjRGS2p59++q51bG1tERYW1gLREFF7wWSEiMwWHh4OO7uGr+7a2tri8ccfR6dOnVowKiJq65iMEJHZ9Ho9xo4d22BCIiKYMmVKC0dFRG0dkxEissiUKVPqvYkVAOzt7fHkk0+2cERE1NYxGSEiizz55JPQ6XR1ytVqNUJDQ+Ho6KhAVETUljEZISKLaDQahIWFQa1Wm5QbDAZMnjxZoaiIqC1jMkJEFps0aRIMBoNJmV6vx2OPPaZQRETUljEZISKLPfrooyYDnanVakycOBH29vYKRkVEbRWTESKymJ2dHSZOnGi8VGMwGDBp0iSFoyKitorJCBE1ysSJE42Xarp27Yrhw4crHBERtVVMRoioUYKCgtCtWzcAwDPPPHPXYeKJiBrCifKaWVpamtIhEDWbBx54AL/99hs6derEvk7tVvfu3TFs2DClw2jXVCIiSgfRnqlUKqVDICKiJoiIiEB6errSYbRn6Twz0gJSU1Px1FNPKR1GqxEZGQkA/HBbIC0tDVFRUWiNfzts374dERERSofRprTm40mmar+vqHnxIi8RNQkTESJqKiYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNtxF/+8hc4OztDpVLh5MmTSofTKuzZswcuLi749NNPlQ6FiIiagMlIG/Huu+/inXfeUTqMVoVjNBARtQ8c9IzarHHjxqGoqEjpMAAA5eXlGD16NI4cOaJ0KEREbQ7PjLQhHFq+9dqyZQsuX76sdBhERG0Sk5FWSkSwbt069O7dGw4ODnBxccH8+fPr1KuursbSpUvh4+MDrVaLgQMHIjU1FQCQnJwMR0dH6HQ67Nq1C2PHjoVer4e3tze2bt1qsp5Dhw7hwQcfhE6ng16vx4ABA1BcXHzXNpRy+PBh+Pj4QKVS4a233gJg/vZu3LgRGo0GXbp0wYwZM+Dl5QWNRoOgoCAcO3bMWC8mJgb29vbw9PQ0lr3wwgtwdHSESqXClStXAACxsbGYN28esrOzoVKpEBAQAADYt28f9Ho9Vq9e3RK7hIiozWIy0kotWbIEcXFxmD59Oi5duoSLFy9iwYIFdeotWLAAa9euRWJiIi5cuIDg4GBMmjQJx48fx6xZszBnzhyUl5fD2dkZqampyM7Ohp+fH6ZNmwaDwQAAKC0tRUhICCIiInD16lVkZWWhV69eqKysvGsbShk+fHidSyLmbm9MTAymTp2KsrIyzJ49Gzk5OThx4gSqqqrw2GOP4fz58wBuJS23zymUlJSE5cuXm5Rt2LABwcHB8Pf3h4jg7NmzAG4lcQBQU1PTLPuAiKi9YDLSCpWXlyMxMRGPPvoo5s6dC1dXV2i1Wri7u5vUq6ioQHJyMkJDQxEeHg5XV1csXrwYarUaKSkpJnWDgoKg1+vh4eGB6OholJaWIjc3FwCQk5OD4uJi9OvXDxqNBl27dsWOHTvQuXNni9poTe60vbXs7OzQt29fODg4IDAwEMnJySgpKbHado0bNw7FxcVYsmSJVdZHRNReMRlphc6ePYuysjKMHj36jvXOnDmDsrIy9O/f31im1Wrh6emJn3/+ucHl7O3tAcB4psDPzw9dunTBlClTsGzZMuTk5DS5jdbk9u1tyJAhQ6DT6drMdhERtRdMRlqhvLw8AICHh8cd65WWlgIAFi9eDJVKZXydO3cOZWVlZren1Wpx4MABDB8+HKtXr4afnx+io6NRXl5utTbaCgcHBxQUFCgdBhFRh8JkpBXSaDQAgJs3b96xXm2ykpiYCBExeR09etSiNvv164dPP/0U+fn5iIuLQ2pqKtavX2/VNlo7g8GA69evw9vbW+lQiIg6FCYjrVD//v1hY2ODQ4cO3bFe9+7dodFomjwia35+Pn766ScAtxKcv/71rxg0aBB++uknq7XRFhw8eBAigqFDhxrL7Ozs7np5h4iImobJSCvk4eGB8PBwbN++HVu2bEFxcTFOnTqFzZs3m9TTaDR47rnnsHXrViQnJ6O4uBjV1dXIy8vDhQsXzG4vPz8fM2bMwM8//4zKykp8//33OHfuHIYOHWq1NlqjmpoaXLt2DVVVVTh16hRiY2Ph4+ODqVOnGusEBATg6tWryMjIgMFgQEFBAc6dO1dnXe7u7sjPz0dOTg5KSkpgMBiwd+9ePtpLRGQOoWYFQFJTUy1erqSkRP7yl79Ip06dxMnJSYYPHy5Lly4VAOLt7S0//PCDiIjcvHlT4uLixMfHR+zs7MTDw0PCw8MlMzNTkpKSRKfTCQDp2bOnZGdny+bNm0Wv1wsA8fX1lV9++UVycnIkKChI3NzcxNbWVv7rv/5LFi1aJFVVVXdtozEiIiIkIiKiUcvWevPNN8XT01MAiE6nk5CQELO3V0Rk+vTpolarpVu3bmJnZyd6vV4mTJgg2dnZJu0UFhbKqFGjRKPRSI8ePeSll16S+fPnCwAJCAiQ3NxcERE5ceKE+Pr6ilarleHDh8vFixdlz5494uzsLKtWrWrStoqIpKamCj+u7QePZ9thje8ruqs0lQgn+GhOKpUKqampdcar6MgiIyMBAOnp6YrFMGPGDKSnp6OwsFCxGCyRlpaGqKgozsfTTvB4th2t4fuqA0jnZRrqsGoHJSMiImUxGSHqAPbv34+FCxdix44d8PPzMz6i/fTTT9epO2bMGDg7O8PW1hb9+vXDiRMnFIjYfCNHjjR57Pz3LycnJ5O6hw8fxkMPPQSdTgcvLy/ExcXd9am1iooK9OnTB4sXLzaWffLJJ1izZo1iCW17Pp5r1qxBnz59oNVq4ejoiD59+mDJkiXG6SlqrVixAoGBgdDr9XBwcEBAQABeeeUV3Lhxw1hH6eNEFlD2MlH7h0beM9KeKX0NduHChWJvby8A5J577pH09HTFYjFXU+4xWLp0qQQHB0txcbGxzN/fXzp16iQA5LPPPquzzN69e2X8+PGNjrcljRgxQgDU+/rv//5vY70ff/xRtFqtLFmyRG7cuCFHjhyRzp07y3PPPXfH9c+dO1cAyKJFi0zKN2zYICNGjJBr165ZHDOPZ8PGjRsn69evl8uXL0tJSYmkpaWJWq2Wxx57zKTeiBEjJCkpSQoLC6W4uFhSU1NFrVbL448/blKvKcfp/2vvTqOiutK9gf8LKKgqqAKMTJEhDCa2Y9qoraht0um42rA0Ig5ETTRZsdGYENTYOPIaokbFC16NLK+JTe5NurVAvZrYaqcTF2alY3uTpUYaOw4kqEgUJGAxKdPzfrCpWBZCFdOh4P9biw+e2ufs5+x9LB7OOXtvEeW/r3qITN4ZoR5n/fr1uHPnDkQEP/zwA6ZOnap0SB1mw4YN2LNnDzIzM6HX6y0+27p1K5ycnBAXF4dbt24pFGHbaTQamEwmq3lw4uLi8Ic//MFc7u2334a/vz/eeustuLu7Y9SoUUhMTMQHH3zwwFl3v/rqK/zzn/9s8rM33ngDQ4YMwbPPPou6uroOObf79YT+dHV1xcKFC+Hj4wMPDw9MmzYNkydPxt/+9jeLEXweHh6Ii4tDr169oNfrMX36dERHR+Po0aPm9aUAZfqJ7MdkhKibunTpElavXo233nrLPJHevSIjI5GQkIBr167hzTffVCDC9nH06FGrX8xXr17FP//5T/zmN78BANTV1eEvf/kLxo0bB5VKZS43YcIEiAgOHjxoddzq6mosXboUW7ZseWDda9aswZkzZ5ot0156Sn/u37/f6vz69OkDABaPYA4dOgRnZ2eLcr179wYAq9mhO7OfqHWYjBB1U1u3boWIYNKkSQ8ss3btWjz66KN4//338dlnnzV7PBFBamqqeXFBb29vTJ482eKuQnp6Otzd3aHT6XDw4EFMmDABBoMBgYGB2L17t8Xx6uvrkZSUhODgYGi1WgwePBhGo7FtJ/1vGzZswBtvvGH+9/fff4+KigoEBwdblAsPDwcAnD171uoYK1euNP+F/iDe3t4YN24ctmzZ0uEjY3pyf168eBFeXl4ICQlptty1a9eg1WoRGhpqsb0z+4lah8kIUTf1l7/8BY899hh0Ot0Dy2i1WnzwwQdwcnLCvHnzzGsRNWXNmjVYvnw5Vq5ciaKiInzxxRe4evUqxo4dixs3bgAAXn31VSxatAjV1dXQ6/UwGo3Iy8tDWFgY5s2bZzGb7bJly7Bp0yakpaXhxx9/xMSJEzFz5kx88803bTrva9euITs7GzExMeZt169fBwCrOygajQZardYcf6O///3vyMvLw8yZM1us75e//CWuXbuGb7/9tk1xt6Sn9WdtbS2uXbuGd999F5999hm2bdtmXvSyKVVVVTh27BjmzZvXZLnO6idqHSYjRN1QZWUlfvjhB/Nf/s0ZNWoUFi1ahPz8fCxbtqzJMtXV1UhNTcWUKVMwe/ZseHp6YtCgQdixYwdu3rxpNTswcPexgcFggI+PD2JjY1FZWYkrV64AuDtCJT09HdHR0YiJiYGXlxdWrVoFtVqNjIyMNp37hg0b8Prrr8PJ6eevt8YRM/ff1gcAtVqN6upqi3NNSEhAenq6TfX17dsXAJCTk9OWsJvVE/szKCgIgYGBWLNmDTZt2oQZM2Y0W379+vUICAjA2rVrm/y8M/qJWs9F6QB6grS0NE6Yc49//OMfAH6eTIha1riSs62KioogIs3+FX2vtWvX4tChQ9i+fXuTX/q5ubmoqKjAsGHDLLYPHz4crq6uOHnyZLPHb/xLtfEv6fPnz6OqqgoDBw40l9FqtfD393/gy6S2KCwsxMcff4yUlBSL7Y3vIDT1AmNNTQ20Wq353ytWrMDvf/9783sKLWls4/vvrrSnntifV69eRVlZGU6fPo3ly5dj586dOHbsGHx9fa3K7t+/H5mZmfj000+t7n416ox+otbjnRGibuj27dsAADc3N5vKazQaZGRkQKVS4eWXX7a4UwAAZWVlAGA1bwcAeHl5oby83K74Gh8frFq1ymJekMuXL1u9fGiPjRs3Yt68eVYvQPr7+wOA1VwVVVVVuH37NgICAgDcnYckJycHr7zyis11NiYyjW3eEXpif6rVavj4+GD8+PHYs2cPcnNzsX79eqtye/bswYYNG5CdnY1HHnnkgcfrjH6i1uOdkU6waNEiTgd/D06vbL/G6cNt1fjFa89kT6NGjcLixYuxefNmvP322xYve3p5eQFAk7+kysrKEBgYaHM9AMwvhaalpSEhIcGufR/k+vXr+POf/4zz589bfRYaGgq9Xm+1yOGlS5cAAIMHDwYA7Nq1C59//rnFI55G69atw7p16/D1119b3FGoqakBAIu7K+2tJ/bnvSIiIuDs7Izc3FyL7du2bcNf//pXHDt2rMnE6l6d0U/UerwzQtQN+fr6QqVS2T3fxNtvv41+/frh9OnTFtsHDhwIDw8Pq5cRT548iZqaGjzxxBN21RMUFASNRoMzZ87YtV9zNm7ciNmzZ6NXr15Wn7m4uODZZ5/FF198gYaGBvP2I0eOQKVSmUeoZGRkWM1XUlxcDODu6BoRsXq00djGfn5+7XYu9+sp/VlSUtLkS8MXL15EfX09goKCANwdCZSYmIicnBwcOHCgxUQE6Jx+otZjMkLUDel0OoSFhdn9rknj7f37X/TUaDRYsmQJ9u/fj48++ggmkwk5OTlYsGABAgICEBcXZ3c9L730Enbv3o309HSYTCbU19ejoKDAPLFVbGws/Pz8bJq+/MaNG/jjH/+IRYsWPbDM6tWrcePGDfy///f/UFlZiRMnTiAlJQVz587FY489Zlf892ps40GDBrX6GC3pKf3p7u6OTz/9FMeOHYPJZEJtbS1Onz6NOXPmwN3dHYsXLwYAnDt3Dps2bcJ7770HtVpttQzA5s2brY7dGf1EbdC5M772POB08FY4vbL9WjN9eHx8vKjVaqmqqjJv279/v4SHhwsA6d27t7z22mtN7rt06VKr6cMbGhokJSVF+vbtK2q1Wry9vSU6OlrOnz9vLrN9+3bR6XQCQPr27St5eXmyc+dOMRgMAkBCQkLkwoULIiJy584dSUxMlODgYHFxcREfHx+JiYmR3NxcERGJjo4WAJKUlNTiuS5evFhmz57dYrnjx4/LiBEjxM3NTQICAmTp0qVy+/btZvcpLi5ucjr4RlFRUdKnTx9paGhosf5GWkiGgwAAIABJREFU7M8HmzRpkoSGhoqHh4e4ublJeHi4xMbGSk5OjrlMTk7OA5cAACApKSlWx21NP4nw+6qTZDIZ6WBMRqzxP7f9WvPL6+LFi+Li4iIffvhhB0XVserr62Xs2LGya9cupUN5oJs3b4pGo5HNmzfbtR/7s3O1tp9E+H3VSbg2DVF3FRERgeTkZCQnJ1tMo+0I6uvrceDAAZSXlyM2NlbpcB5ozZo1ePzxxxEfH9/hdbE/W68z+4lah8lIF3L/cuCNP66urvD19cWTTz6JlJQUlJaWKh0qOYjly5dj2rRpiI2NdajF07Kzs7Fv3z4cOXLE5rk1OltqairOnDmDw4cPQ61Wd0qd7E/7KdFPZD8mI11ITEwMvv/+e4SHh8PT0xMigoaGBhQVFSEzMxOhoaFITEzEgAED2jxlNvUc69atQ3x8PN555x2lQ7HZ008/jT/96U/m+UG6moMHD+LOnTvIzs6Gt7d3p9bN/rSdkv1E9mEy0sWpVCp4eXnhySefREZGBjIzM3Hjxg1ERUU51F9GXU11dTUiIyMdvg5bjR8/Hhs2bFA6jG7jueeew/Lly5ucXr4zsD9to3Q/ke2YjDiYqVOnYu7cuSgqKsKOHTuUDsdh7dq1C0VFRQ5fBxFRd8BkxAHNnTsXwN0Jmxo1t3y3PcuAHz9+HCNGjIBOp4PBYMCgQYPMU2h35BLhLREbljuPj4+Hq6urxa3ghQsXwt3dHSqVCjdv3gQAJCQkYMmSJcjLy4NKpUJERAS2bt0KjUYDX19fzJ8/HwEBAdBoNIiMjLRYp6MtdQDA0aNHYTAYsG7dug5tLyIih6L0eJ7uDq0Y2hseHi6enp4P/NxkMgkACQoKMm978803xc3NTfbu3SulpaWyYsUKcXJykq+//lpERFauXCkA5PPPP5dbt25JUVGRjB07Vtzd3aWmpkZERCoqKsRgMMjGjRulurparl+/LlOmTJHi4mKb6rBVa4bKJSUliaurq3z44YdSVlYmZ8+elaFDh0rv3r3l+vXr5nKzZs0SPz8/i31TUlIEgPk8RERiYmIkPDzcolxcXJy4u7vLuXPn5Pbt25KbmyvDhw8XvV4vV65caZc6Dh06JHq9XpKTk+06/9YMBaWui/3pODi0t1NwaK8j0uv1UKlU5nUl7Fm+u7llwPPz82EymTBgwABoNBr4+flh37596N27d4cu+d6S1ix33louLi7muy/9+/dHeno6ysvL2+0co6KiYDKZsHr16nY5HhFRd8BkxAFVVlZCRGAwGAC0fvnu+5cBDwsLg6+vL2bPno01a9YgPz/fXLajlny3RVuXO2+LYcOGQafTdfg5EhH1ZExGHNCFCxcAAP369QPQfst3a7VaHDt2DGPGjMG6desQFhaG2NhYVFdXd9iS77Zo7+XO7eXm5mZeLI2IiNofkxEHdPToUQDAhAkTAFgu3y33rTh64sQJu449YMAAfPLJJygsLERiYiKMRiM2b97crnXYq72XO7dHbW1th9dBRNTTMRlxMNevX0daWhoCAwPx8ssvA2i/5bsLCwtx7tw5AHcTnHfeeQdDhw7FuXPnOmTJd1vZs9y5i4uL+bFTe8jOzoaIYOTIkR1WBxFRT8dkpIsSEVRUVKChoQEiguLiYhiNRowePRrOzs44cOCA+Z0RW5bvtkVhYSHmz5+P7777DjU1NTh9+jQuX76MkSNHtlsdrWHPcucRERH46aefcODAAdTW1qK4uBiXL1+2OmavXr1QWFiI/Px8lJeXm5OLhoYGlJaWoq6uDmfPnkVCQgKCg4PNw6nbWseRI0c4tJeI6H7KjOLpOWDH0N6PP/5YBg8eLDqdTlxdXcXJyUkAiEqlEi8vLxkxYoQkJydLSUmJ1b7NLd9t6zLg+fn5EhkZKd7e3uLs7CwPP/ywrFy5Uurq6lqswx6tGSpny3LnIiIlJSXy1FNPiUajkdDQUHn99ddl6dKlAkAiIiLMQ3RPnTolISEhotVqZcyYMXL9+nWJi4sTtVotffr0ERcXFzEYDDJ58mTJy8trtzoOHz4ser1e1q5da9f5cyho98L+dBwc2tspMlUiIsqlQt2fSqWC0WjE9OnTlQ6ly5g2bRoAICsrS+FILM2fPx9ZWVkoKSlROhQrmZmZmDFjBvjftXtgfzqOrvp91c1k8TEN0T3q6+uVDoGIqMdhMkJERESKYjJCBGDFihXIyMjArVu3EBoair179yodEhFRj+GidABEXcH69euxfv16pcMgIuqReGeEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFGVg7mEqlUjoEIiJqg6lTp3IG1o6VxaG9HcxoNCodAlGHOXHiBLZs2cLrnLq1oKAgpUPo9nhnhIhajWusEFE74No0REREpCwmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI0RERKQoF6UDICLHUFxcjP/93/+12PbNN98AAHbu3GmxXa/X4/nnn++02IjIsalERJQOgoi6vjt37sDX1xcVFRVwdnYGADR+fahUKnO52tpazJkzBx988IESYRKR48niYxoisombmxumTp0KFxcX1NbWora2FnV1dairqzP/u7a2FgAwc+ZMhaMlIkfCZISIbDZz5kzU1NQ0W8bLywu/+c1vOikiIuoOmIwQkc2eeuop+Pj4PPBztVqN2bNnw8WFr6MRke2YjBCRzZycnDBr1iyo1eomP6+treWLq0RkNyYjRGSX559/3vxuyP0efvhhjBo1qpMjIiJHx2SEiOwyYsQIhISEWG13dXXFnDlzLEbWEBHZgskIEdnthRdesHpUU1NTw0c0RNQqTEaIyG6zZs2yelQTERGBQYMGKRQRETkyJiNEZLd+/fqhf//+5kcyarUaL730ksJREZGjYjJCRK3y4osvmmdiraur4yMaImo1JiNE1CrPP/886uvrAQBDhw5FaGiowhERkaNiMkJErRIcHIxf/epXAIA5c+YoHA0ROTJOk2inadOmKR0CUZdx584dqFQqfPrpp/jiiy+UDoeoSxg1ahQWL16sdBgOhXdG7LR3714UFBQoHQbdp6CgAHv37lU6DIfT1us5MDAQfn5+0Gg07RgV3Y/Xt+P4xz/+gRMnTigdhsNRSeMa4GQTlUoFo9GI6dOnKx0K3SMzMxMzZswAL2f7tMf1fOnSJURERLRjVHQ/Xt+Oo/HueVZWlsKROJQs3hkhojZhIkJEbcVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZKSTvfLKK9Dr9VCpVDhz5ozS4XQJDQ0NSEtLQ2RkpNKh4PDhw/D09MQnn3yidChERD0Gk5FO9v777+O9995TOowu4+LFi/j1r3+NxYsXo6qqSulwOHSSiEgBTEaoTaqrq1t9R+Pbb7/FsmXLsGDBAjz++OPtHFnrREVF4datW5g4caLSobSpbYmIHAmTEQU0LrveHezatQtFRUWt2nfIkCHYt28fZs2aBTc3t3aOzPG1pW2JiBwJk5EOJiJISUnBY489Bjc3N3h6emLp0qUWZTZt2gSdTge9Xo+ioiIsWbIEffr0wfnz5yEiSE1NxS9+8Qu4ubnB29sbkydPxnfffWfef+vWrdBoNPD19cX8+fMREBAAjUaDyMhInDx50iqelo4XHx8PV1dX+Pv7m7ctXLgQ7u7uUKlUuHnzJgAgISEBS5YsQV5eHlQqlcNPfvXll18iODgYKpUK7777LgAgPT0d7u7u0Ol0OHjwICZMmACDwYDAwEDs3r3bvK+tfdDWtj169CgMBgPWrVvXGU1CRNQ5hOwCQIxGo83lV65cKSqVSv7jP/5DSktLpaqqSrZv3y4A5PTp0xblAMgbb7wh27ZtkylTpsi//vUvSUpKEldXV/nwww+lrKxMzp49K0OHDpXevXvL9evXzfvHxcWJu7u7nDt3Tm7fvi25ubkyfPhw0ev1cuXKFXM5W483a9Ys8fPzsziXlJQUASDFxcXmbTExMRIeHm5XGzblV7/6lQwZMqTV+xuNRmmPy/nq1asCQLZt22be1tg3n3/+udy6dUuKiopk7Nix4u7uLjU1NeZytvZBW9r20KFDotfrJTk5uc3nKmL/9UzKaK/rmzre1KlTZerUqUqH4WgyeWekA1VXVyMtLQ2//e1vsXjxYnh5eUGr1aJXr14P3GfDhg147bXXsG/fPoSEhCA1NRVTpkzB7Nmz4enpiUGDBmHHjh24efMmdu7cabGvi4uL+Y5H//79kZ6ejvLycmRkZJjjsed4ZCkyMhIGgwE+Pj6IjY1FZWUlrly5YlGmpT5oq6ioKJhMJqxevbpdjkdE1BUwGelAly5dQlVVFZ5++ulW7Z+bm4uKigoMGzbMYvvw4cPh6upq9QjmfsOGDYNOpzM/gmnr8ehnrq6uAIDa2tpmy93fB0REZI3JSAdqXJrdx8enVfuXlZUBADw8PKw+8/LyQnl5eYvHcHNzQ3Fxcbsdj+x3bx8QEZE1JiMdSKPRAADu3LnTqv29vLwAoMkkoaysDIGBgc3uX1tba1Gurccj+93fB0REZI3JSAcaOHAgnJyccPz48Vbv7+HhgW+++cZi+8mTJ1FTU4Mnnnii2f2zs7MhIhg5cqTdx3NxcWnxEQS17P4+ANi2RET3YzLSgXx8fBATE4O9e/di165dMJlMOHv2rM0vimo0GixZsgT79+/HRx99BJPJhJycHCxYsAABAQGIi4uzKN/Q0IDS0lLU1dXh7NmzSEhIQHBwMObOnWv38SIiIvDTTz/hwIEDqK2tRXFxMS5fvmwVY69evVBYWIj8/HyUl5f3+F+yLfUB0La2PXLkCIf2ElH3o/R4HkcDO4dClpeXyyuvvCIPPfSQeHh4yJgxYyQpKUkASGBgoHz77beyceNG0Wq1AkCCgoLkww8/NO/f0NAgKSkp0rdvX1Gr1eLt7S3R0dFy/vx5i3ri4uJErVZLnz59xMXFRQwGg0yePFny8vIsytl6vJKSEnnqqadEo9FIaGiovP7667J06VIBIBEREeahqqdOnZKQkBDRarUyZswYi+HBLTlx4oSMHj1aAgICBIAAEH9/f4mMjJTjx4/bfByR9hn6uG3bNvH39xcAotPpZNKkSbJ9+3bR6XQCQPr27St5eXmyc+dOMRgMAkBCQkLkwoULImJ7H7SlbQ8fPix6vV7Wrl3bpnNtZO/1TMrg0F7HwaG9rZKpEuFiHPZQqVQwGo2YPn260qFYmD9/PrKyslBSUqJ0KIrIzMzEjBkzFF1bxhH7oKtez2SpK1zfZJtp06YBALKyshSOxKFk8TFNN1JfX690CD0e+4CIyH5MRqjdfPfdd1CpVC3+xMbGKh0qERF1IUxGuoEVK1YgIyMDt27dQmhoKPbu3atIHP369YOItPizZ88eReLrSF2lDzrTZ599huXLl2Pfvn0ICwszJ5svvPCCVdnx48dDr9fD2dkZAwYMwKlTpxSI2HYbN25Ev379oNVq4e7ujn79+mH16tUwmUwW5ZKTk9G/f38YDAa4ubkhIiICf/jDH1BRUWEu8/HHH2Pjxo2K3jVjXzlOX/VYiryq4sDAF/66JL7g1zqtvZ6TkpJk4sSJYjKZzNvCw8PloYceEgBy6NAhq32OHDkizz33XJvi7SxRUVGyefNmKSoqkvLycsnMzBS1Wi3PPPOMRblx48bJ9u3bpaSkREwmkxiNRlGr1fK73/3OotyWLVtk3LhxUlpa2qp42nJ9s6/u6qy+4gusrcK1aYjIPhs2bMCePXuQmZkJvV5v8dnWrVvh5OSEuLg43Lp1S6EI287V1RULFy6Ej48PPDw8MG3aNEyePBl/+9vf8OOPP5rLeXh4IC4uDr169YJer8f06dMRHR2No0eP4urVq+Zyb7zxBoYMGYJnn30WdXV1nXYe7CvH6auejskIEdns0qVLWL16Nd566y3zDMP3ioyMREJCAq5du4Y333xTgQjbx/79+63Or0+fPgBgcVv/0KFDcHZ2tijXu3dvAEBVVZXF9jVr1uDMmTPYsmVLR4RshX3lOH1FTEaIyA5bt26FiGDSpEkPLLN27Vo8+uijeP/99/HZZ581ezwRQWpqqnmlY29vb0yePNliYcH09HS4u7tDp9Ph4MGDmDBhAgwGAwIDA7F7926L49XX1yMpKQnBwcHQarUYPHgwjEZj20763y5evAgvLy+EhIQ0W+7atWvQarUIDQ212O7t7Y1x48Zhy5YtnTJEl33lOH1F4EN2e4HvjHRJfGekdey9nsPCwqR///5NfhYeHi4//PCDiIh89dVX4uTkJI888ohUVFSISNPvISQlJYmrq6t8+OGHUlZWJmfPnpWhQ4dK7969LSbQW7lypQCQzz//XG7duiVFRUUyduxYcXd3l5qaGnO5N998U9zc3GTv3r1SWloqK1asECcnJ/n6669tPsd71dTUSEFBgWzbtk3c3NwsJiRsSmVlpej1eomPj2/y8+XLlwsAOX36tF1xtOb6Zl8p01d8Z6RVMvntbScmI10Tk5HWsed6rqioEJVKJRMnTmzy83t/wYmILFmyRADIa6+9JiLWv+CqqqrEw8NDYmNjLY7zf//3fwJAkpOTzdsaf8FVV1ebt23fvl0AyKVLl0REpLq6WnQ6ncXxqqqqxM3NTV599VWbzvF+fn5+AkAeeugh+c///E+LX6ZNWblypTz66KMWL4ve649//KMAkP/5n/+xKw57r2/2lXJ9xWSkVfgCa2vMmDHDpvk0+NN5PzNmzAAAxeNwtB97FBUVQUSg0+lsKr927Vo89thj2L59O7788kurz3Nzc1FRUYFhw4ZZbB8+fDhcXV1x8uTJZo/v6uoKAOb1kM6fP4+qqioMHDjQXEar1cLf39/iUYI9rl69iqKiIvz5z3/Gf//3f+OXv/wlioqKmiy7f/9+ZGZm4q9//avVy6KNGtvuxo0brYrHVuwrx+krustF6QAcUUJCAkaNGqV0GHSPEydOYMuWLe32zLmnaEzibHH79m0AgJubm03lNRoNMjIyMGbMGLz88svYuHGjxedlZWUA7o5yuJ+XlxfKy8ttjg0AKisrAQCrVq3CqlWrLD4LCAiw61iN1Go1fHx8MH78eISGhuLRRx/F+vXrrV5s3LNnD1JTU5GdnY2HH374gcfTarUAfm7LjsK+cpy+oruYjLTCqFGjuJZHF7Rlyxb2i53sSUYav5ztmRBq1KhRWLx4MTZv3oy3334bwcHB5s+8vLwAoMlfZGVlZQgMDLS5HuDuKtkAkJaWhoSEBLv2tUVERAScnZ2Rm5trsX3btm3461//imPHjjX5y/peNTU1AH5uy47CvnKcvqK7+JiGiGzi6+sLlUpl95wUb7/9Nvr164fTp09bbB84cCA8PDzwzTffWGw/efIkampq8MQTT9hVT1BQEDQaDc6cOWPXfvcrKSnBzJkzrbZfvHgR9fX1CAoKAnB3dEliYiJycnJw4MCBFn+5ATC3nZ+fX5tibAn7ynH6iu5iMkJENtHpdAgLC0NBQYFd+zU+Arh/jgeNRoMlS5Zg//79+Oijj2AymZCTk4MFCxYgICAAcXFxdtfz0ksvYffu3UhPT4fJZEJ9fT0KCgrMk1/FxsbCz8+v2SnO3d3d8emnn+LYsWMwmUyora3F6dOnMWfOHLi7u2Px4sUAgHPnzmHTpk147733oFarrd7H2bx5s9WxG9tu0KBBdp2bvdhXjtNX9G/KvkDreMDRNF0SR9O0jr3Xc3x8vKjVaqmqqjJv279/v4SHhwsA6d27t3lExv2WLl1qNVy0oaFBUlJSpG/fvqJWq8Xb21uio6Pl/Pnz5jLbt28XnU4nAKRv376Sl5cnO3fuFIPBIAAkJCRELly4ICIid+7ckcTERAkODhYXFxfx8fGRmJgYyc3NFRGR6OhoASBJSUnNnuekSZMkNDRUPDw8xM3NTcLDwyU2NlZycnLMZXJycgTAA39SUlKsjhsVFSV9+vSRhoaGFlraUmuub/aVMn3F0TStwqG99mIy0jUxGWkde6/nixcviouLS4tzOHRV9fX1MnbsWNm1a1en133z5k3RaDSyefNmu/dtzfXNvmq9tvQVk5FW4dBeIrJdREQEkpOTkZycbDHVtiOor6/HgQMHUF5ejtjY2E6vf82aNXj88ccRHx/fKfWxr1qvs/uK+M6Iou5fzrvxx9XVFb6+vnjyySeRkpKC0tJSpUMlMlu+fDmmTZuG2NhYh1pgLTs7G/v27cORI0dsnn+jvaSmpuLMmTM4fPgw1Gp1p9XLvrKfUn3V0zEZUVBMTAy+//57hIeHw9PTEyKChoYGFBUVITMzE6GhoUhMTMSAAQOs3mInUtK6desQHx+Pd955R+lQbPb000/jT3/6E/z9/Tu13oMHD+LOnTvIzs6Gt7d3p9YNsK/soXRf9WRMRroYlUoFLy8vPPnkk8jIyEBmZiZu3LiBqKgoh/rL5kGqq6sRGRmpdBgdojPOrSu13/jx47Fhwwalw+jynnvuOSxfvtxqhEpnYl/Zpiv0VU/FZKSLmzp1KubOnYuioiLs2LFD6XDabNeuXQ+cotnRdca5def2I6Kei8mIA5g7dy4A4MiRIwCATZs2QafTQa/Xo6ioCEuWLEGfPn1w/vx5m5b53rp1KzQaDXx9fTF//nwEBARAo9EgMjLSao0JW44XHx8PV1dXi1uqCxcuhLu7O1QqFW7evAng7jT6S5YsQV5eHlQqFSIiIjqqyWzS0edmazu3tf2OHj0Kg8GAdevWdWh7ERF1GGVH8zgedMDQ3vDwcPH09Hzg5yaTSQBIUFCQeVvjyphvvPGGbNu2TaZMmSL/+te/bF7mOy4uTtzd3eXcuXNy+/Ztyc3NleHDh4ter5crV66Yy9l6vFmzZomfn59F3CkpKQJAiouLzdtiYmIkPDy8Te3VlNYMfeyMc7O1ndtSx6FDh0Sv11usnGqrjrieqf1x6Lrj4NDeVuHQXkeg1+uhUqmaXBdiw4YNeO2117Bv3z6EhIQgNTUVU6ZMwezZs+Hp6YlBgwZhx44duHnzJnbu3Gmxr4uLi/muQP/+/ZGeno7y8nJkZGQAuPt+gj3HcySdeW4ttXNbRUVFwWQyYfXq1e1yPCKizsZkxAFUVlZCRGAwGJot19ZlvocNGwadTmd+TNHW43VlSp7b/e1MRNTTMRlxABcuXAAA9OvXr9ly7bHMt5ubG4qLi9vteF2V0ud2bzsTEfV0TEYcwNGjRwEAEyZMaLZcW5f5rq2ttSjX3suGdyVKntv97UxE1NMxGenirl+/jrS0NAQGBuLll19utmxbl/nOzs6GiGDkyJF2H8/FxQW1tbX2nJqilDy3+9u5I+ogInIkTEa6CBFBRUUFGhoaICIoLi6G0WjE6NGj4ezsjAMHDrT4zoi9y3w3NDSgtLQUdXV1OHv2LBISEhAcHGweSmzP8SIiIvDTTz/hwIEDqK2tRXFxMS5fvmwVY69evVBYWIj8/HyUl5cr9gu4M8+tpXZuax1Hjhzh0F4icmyKDuZxQGjHoZAff/yxDB48WHQ6nbi6uoqTk5MAEJVKJV5eXjJixAhJTk6WkpISi/02btwoWq3WPNz33lU5bVnmW+TukFO1Wi19+vQRFxcXMRgMMnnyZMnLy7MoZ+vxSkpK5KmnnhKNRiOhoaHy+uuvy9KlSwWAREREmIexnjp1SkJCQkSr1cqYMWMshtC2RWuGPnbGudnazm2p4/Dhw6LX62Xt2rV2t1t7Xs/UcTi013FwaG+rZKpERBTLhByQSqWC0WjE9OnTlQ6lTebPn4+srCyUlJQoHUq7yMzMxIwZM9DVLueu3s7d5Xru7rrq9U3Wpk2bBgDIyspSOBKHksXHND1YfX290iH0CGxnIqLmMRkhIiIiRTEZ6YFWrFiBjIwM3Lp1C6Ghodi7d6/SIXVLbGciItu4KB0Adb7169dj/fr1SofR7bGdiYhswzsjREREpCgmI0RERKQoJiNERESkKCYjREREpCi+wNoKJ06cUDoEuk9jn2RmZiociePh9dz18fp2HAUFBVwEsxU4A6udVCqV0iEQEVEXNnXqVM7Aap8s3hmxE3M3op9xmnIiag98Z4SIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTFZISIiIgUxWSEiIiIFMVkhIiIiBTlonQAROQYCgoKMGfOHNTX15u3lZaWQq/X48knn7Qo+9hjj+G//uu/OjlCInJUTEaIyCaBgYG4fPky8vLyrD47fvy4xb9//etfd1ZYRNQN8DENEdnsxRdfhFqtbrFcbGxsJ0RDRN0FkxEistmsWbNQV1fXbJkBAwagf//+nRQREXUHTEaIyGbh4eEYPHgwVCpVk5+r1WrMmTOnk6MiIkfHZISI7PLiiy/C2dm5yc/q6uowbdq0To6IiBwdkxEissvzzz+PhoYGq+1OTk4YOXIkHnnkkc4PiogcGpMRIrJLQEAARo8eDSe1FjPTAAAYpUlEQVQny68PJycnvPjiiwpFRUSOjMkIEdnthRdesNomIpgyZYoC0RCRo2MyQkR2mzp1qsV7I87Ozvjtb38LX19fBaMiIkfFZISI7Obt7Y1nnnnGnJCICGbPnq1wVETkqJiMEFGrzJ492/wiq1qtxuTJkxWOiIgcFZMRImqVSZMmwc3NDQAwceJEeHh4KBwRETkqJiNE1Cru7u7muyF8RENEbaESEVE6iO4kMzMTM2bMUDoMIiLqIPy12e6yuGpvBzEajUqH0K3MmDEDCQkJGDVqlNKhOIy0tDQAwKJFizqsjvr6ehiNRsycObPD6ugJeH07hhMnTmDLli1Kh9Et8c5IO2u8M8JmbV8qlQpGoxHTp09XOhSH0Tgte1ZWVofWc/v2bWg0mg6to7vj9e0Y+P3eYbL4zggRtQkTESJqKyYjREREpCgmI0RERKQoJiNERESkKCYjREREpCgmI13QK6+8Ar1eD5VKhTNnzigdTps0NDQgLS0NkZGRSocCADh8+DA8PT3xySefKB0KERH9G5ORLuj999/He++9p3QYbXbx4kX8+te/xuLFi1FVVaV0OAA4WRERUVfESc+oQ3z77bdITk7GggULUFlZ2WWSgKioKNy6dUvpMAAA1dXVePrpp/HVV18pHQoRkaJ4Z6SLUqlUSofQJkOGDMG+ffswa9Ys82JqZGnXrl0oKipSOgwiIsUxGekCRAQpKSl47LHH4ObmBk9PTyxdutSqXH19PZKSkhAcHAytVovBgwebp51PT0+Hu7s7dDodDh48iAkTJsBgMCAwMBC7d++2OM7x48cxYsQI6HQ6GAwGDBo0CCaTqcU6HN2XX36J4OBgqFQqvPvuuwBsb7etW7dCo9HA19cX8+fPR0BAADQaDSIjI3Hy5Elzufj4eLi6usLf39+8beHChXB3d4dKpcLNmzcBAAkJCViyZAny8vKgUqkQEREBADh69CgMBgPWrVvXGU1CRNQlMBnpAlavXo3ExETExcXhxo0buH79OpYtW2ZVbtmyZdi0aRPS0tLw448/YuLEiZg5cya++eYbvPrqq1i0aBGqq6uh1+thNBqRl5eHsLAwzJs3D7W1tQCAyspKTJo0CVOnTsVPP/2Eixcv4tFHH0VNTU2LdTi6MWPGWD0SsbXd4uPjMXfuXFRVVeGNN95Afn4+Tp06hbq6OjzzzDO4evUqgLtJy/1Tem/fvh1vvfWWxbYtW7Zg4sSJCA8Ph4jg0qVLAO4mg8DdF3+JiHoKJiMKq66uRlpaGn77299i8eLF8PLyglarRa9evSzK3b59G+np6YiOjkZMTAy8vLywatUqqNVqZGRkWJSNjIyEwWCAj48PYmNjUVlZiStXrgAA8vPzYTKZMGDAAGg0Gvj5+WHfvn3o3bu3XXV0R821WyMXFxf84he/gJubG/r374/09HSUl5e3W/tERUXBZDJh9erV7XI8IiJHwGREYZcuXUJVVRWefvrpZsudP38eVVVVGDhwoHmbVquFv78/vvvuuwfu5+rqCgDmv/DDwsLg6+uL2bNnY82aNcjPz29zHd3R/e32IMOGDYNOp+tx7UNE1J6YjCisoKAAAODj49NsucrKSgDAqlWroFKpzD+XL1+2a9isVqvFsWPHMGbMGKxbtw5hYWGIjY1FdXV1u9XR07i5uaG4uFjpMIiIHBaTEYU1rnh6586dZss1JitpaWkQEYufEydO2FXngAED8Mknn6CwsBCJiYkwGo3YvHlzu9bRU9TW1qKsrAyBgYFKh0JE5LCYjChs4MCBcHJywvHjx5stFxQUBI1G0+YZWQsLC3Hu3DkAdxOcd955B0OHDsW5c+farY6eJDs7GyKCkSNHmre5uLi0+HiHiIh+xmREYT4+PoiJicHevXuxa9cumEwmnD17Fjt37rQop9Fo8NJLL2H37t1IT0+HyWRCfX09CgoK8OOPP9pcX2FhIebPn4/vvvsONTU1OH36NC5fvoyRI0e2Wx3dWUNDA0pLS1FXV4ezZ88iISEBwcHBmDt3rrlMREQEfvrpJxw4cAC1tbUoLi7G5cuXrY7Vq1cvFBYWIj8/H+Xl5aitrcWRI0c4tJeIeh6hdmU0GsXeZi0vL5dXXnlFHnroIfHw8JAxY8ZIUlKSAJDAwED59ttvRUTkzp07kpiYKMHBweLi4iI+Pj4SExMjubm5sn37dtHpdAJA+vbtK3l5ebJz504xGAwCQEJCQuTChQuSn58vkZGR4u3tLc7OzvLwww/LypUrpa6ursU67HHixAkZPXq0BAQECAABIP7+/hIZGSnHjx+361giIgDEaDTavd+9tm3bJv7+/gJAdDqdTJo0yeZ2ExGJi4sTtVotffr0ERcXFzEYDDJ58mTJy8uzqKekpESeeuop0Wg0EhoaKq+//rosXbpUAEhERIRcuXJFREROnTolISEhotVqZcyYMXL9+nU5fPiw6PV6Wbt2bZvOVURk6tSpMnXq1DYfhzpee1zf1PFa8/1ONslUiXSRebq7iczMTMyYMaPLTH/eXahUKhiNRqs5PDrT/PnzkZWVhZKSEsVisMe0adMAAFlZWQpHQi3pCtc3tYzf7x0mi49piOzQOCkZERG1HyYjZJPvvvvOYrjvg35iY2OVDpXayWeffYbly5dj3759CAsLM/fxCy+8YFV2/Pjx0Ov1cHZ2xoABA3Dq1CkFIrbdxo0b0a9fP2i1Wri7u6Nfv35YvXq1eVmERsnJyejfvz8MBgPc3NwQERGBP/zhD6ioqDCX+fjjj7Fx40bFEtXu3E+NGhoakJaWhsjISJvK3759G/369cOqVavM25TuJ2qBso+Juh8+U+wYUPiZ+vLly8XV1VUAyCOPPCJZWVmKxWKrtrwzkpSUJBMnThSTyWTeFh4eLg899JAAkEOHDlntc+TIEXnuuedaHW9nioqKks2bN0tRUZGUl5dLZmamqNVqeeaZZyzKjRs3TrZv3y4lJSViMpnEaDSKWq2W3/3udxbltmzZIuPGjZPS0tJWxdPa67u795OIyIULF2T06NECQIYMGWLTPosXLxYAsnLlSovtbe0nfr93mEzeGSGywfr163Hnzh2ICH744QdMnTpV6ZA6zIYNG7Bnzx5kZmZCr9dbfLZ161Y4OTkhLi4Ot27dUijCtnN1dcXChQvh4+MDDw8PTJs2DZMnT8bf/vY3i5FjHh4eiIuLQ69evaDX6zF9+nRER0fj6NGj5vWIAOCNN97AkCFD8Oyzz6Kurq5TzqEn9NO3336LZcuWYcGCBXj88cdt2uerr77CP//5zyY/U6KfyDZMRojI7NKlS1i9ejXeeust84R894qMjERCQgKuXbuGN998U4EI28f+/futzq9Pnz4AYPEI5tChQ3B2drYo17t3bwCwmpV4zZo1OHPmDLZs2dIRIVvoKf00ZMgQ7Nu3D7NmzYKbm1uL5aurq7F06dJm+6Az+4lsx2SEiMy2bt0KEcGkSZMeWGbt2rV49NFH8f777+Ozzz5r9ngigtTUVPPigt7e3pg8ebLFWj7p6elwd3eHTqfDwYMHMWHCBBgMBgQGBmL37t0Wx6uvr0dSUhKCg4Oh1WoxePBgGI3Gtp30v128eBFeXl4ICQlptty1a9eg1WoRGhpqsd3b2xvjxo3Dli1bOny0RU/up+asXLnSfMfrQTqzn8h2TEaIyOwvf/kLHnvsMeh0ugeW0Wq1+OCDD+Dk5IR58+aZ1zRqypo1a7B8+XKsXLkSRUVF+OKLL3D16lWMHTsWN27cAAC8+uqrWLRoEaqrq6HX62E0GpGXl4ewsDDMmzfPYjbbZcuWYdOmTUhLS8OPP/6IiRMnYubMmfjmm29adb61tbW4du0a3n33XXz22WfYtm2beZHEplRVVeHYsWOYN29ek+V++ctf4tq1a/j2229bFY+telo/2eLvf/878vLyMHPmzBbLdlY/ke2YjBARgLuLMf7www8IDw9vseyoUaOwaNEi5OfnY9myZU2Wqa6uRmpqKqZMmYLZs2fD09MTgwYNwo4dO3Dz5k2rWYaBu48XDAYDfHx8EBsbi8rKSly5cgXA3RES6enpiI6ORkxMDLy8vLBq1Sqo1WpkZGS06pyDgoIQGBiINWvWYNOmTZgxY0az5devX4+AgACsXbu2yc/79u0LAMjJyWlVPLboif3UkurqaiQkJCA9Pd2m8p3RT2QfF6UD6K4yMzOVDqHb4WJ99ikoKLBrAb+ioiKISLN/bd9r7dq1OHToELZv397kL/Hc3FxUVFRg2LBhFtuHDx8OV1dXnDx5stnjN955aPyL+/z586iqqsLAgQPNZbRaLfz9/S0eJ9jj6tWrKCsrw+nTp7F8+XLs3LkTx44dg6+vr1XZ/fv3IzMzE59++qnVC6ONGtuu8W5CR+iJ/dSSFStW4Pe//735vZ+WdEY/kX2YjHSQlv7CIvtt2bKFL53ZyZ5RP7dv3wYAm14UBO6ul5SRkYExY8bg5ZdfxsaNGy0+LysrA3B3RMr9vLy8UF5ebnNsAMyPGVatWmUxfwQABAQE2HWsRmq1Gj4+Phg/fjxCQ0Px6KOPYv369VbX2Z49e5Camors7Gw8/PDDDzyeVqsF8HNbdoSe2E/N+fLLL5GTk4PU1FSb9+mMfiL78DFNBxER/rTjDwAYjUbF43CkH3uHHzd+QdszKdSoUaOwePFiXLx4EW+//bbFZ15eXgDQ5C+zsrIyu+7aADC/lJiWlmZ1ru1x1ywiIgLOzs7Izc212L5t2zZ89NFHOHbsWLOJCADU1NQA+LktO0JP76f77dq1C59//jmcnJzME741xrBu3TqoVCqrd1U6o5/IPkxGiAgA4OvrC5VKZfe8FG+//Tb69euH06dPW2wfOHAgPDw8rH4RnDx5EjU1NXjiiSfsqicoKAgajQZnzpyxa7/7lZSUNPmS48WLF1FfX4+goCAAd/+gSExMRE5ODg4cONDknYP7Nbadn59fm2JsTk/pJ1tlZGRYJT3FxcUA7o6uERGrR1Cd0U9kHyYjRATg7nP0sLAwFBQU2LVf42OA++fj0Gg0WLJkCfbv34+PPvoIJpMJOTk5WLBgAQICAhAXF2d3PS+99BJ2796N9PR0mEwm1NfXo6CgwDxRWWxsLPz8/Jqd5tzd3R2ffvopjh07BpPJhNraWpw+fRpz5syBu7s7Fi9eDAA4d+4cNm3ahPfeew9qtdpq6YPNmzdbHbux7QYNGmTXudmjp/RTR+qMfiI7CbUrThfcMcAl1u3Wmung4+PjRa1WS1VVlXnb/v37JTw8XABI79695bXXXmty36VLl1pNM97Q0CApKSnSt29fUavV4u3tLdHR0XL+/Hlzme3bt4tOpxMA0rdvX8nLy5OdO3eKwWAQABISEiIXLlwQEZE7d+5IYmKiBAcHi4uLi/j4+EhMTIzk5uaKiEh0dLQAkKSkpGbPc9KkSRIaGioeHh7i5uYm4eHhEhsbKzk5OeYyOTk5AuCBPykpKVbHjYqKkj59+khDQ0MLLW3J3uu7p/TTiRMnZPTo0RIQEGBud39/f4mMjJTjx48/cL/i4uImp4Nv1Np+4vd7h8lkq7YzXqwdg8mI/VqTjFy8eFFcXFzkww8/7KCoOlZ9fb2MHTtWdu3a1el137x5UzQajWzevNnufe29vtlPrdeWfuL3e4fh2jRE9LOIiAgkJycjOTnZYlp0R1BfX48DBw6gvLxckdWj16xZg8cffxzx8fEdXhf7qfU6s5/IdkxGiMjC8uXLMW3aNMTGxjrUImvZ2dnYt28fjhw5YvMcHO0lNTUVZ86cweHDh6FWqzulTvaT/ZToJ7INk5Eubt++fQgLC7N6ec7V1RW+vr548sknkZKSgtLSUqVDpW5k3bp1iI+PxzvvvKN0KDZ7+umn8ac//Qn+/v6dWu/Bgwdx584dZGdnw9vbu1PrZj/ZTsl+opYxGeniYmJi8P333yM8PByenp4QETQ0NKCoqAiZmZkIDQ1FYmIiBgwY0KHrPlDPM378eGzYsEHpMLq85557DsuXL7capdJZ2E+2UbqfqHlMRhyQSqWCl5cXnnzySWRkZCAzMxM3btxAVFSUQ92udSTV1dWIjIx0+DqIiLoiJiPdwNSpUzF37lwUFRVhx44dSofTLe3atQtFRUUOXwcRUVfEZKSbmDt3LgDgyJEj5m319fVISkpCcHAwtFotBg8eDKPRCABIT0+Hu7s7dDodDh48iAkTJsBgMCAwMBC7d++2OPbx48cxYsQI6HQ6GAwGDBo0CCaTqcU6lCQiSE1NxS9+8Qu4ubnB29sbkydPtlioKz4+Hq6urhbPrhcuXAh3d3eoVCrcvHkTAJCQkIAlS5YgLy8PKpUKERER2Lp1KzQaDXx9fTF//nwEBARAo9EgMjLSYmGxttQBAEePHoXBYMC6des6tL2IiBSl9ODi7qajxqGHh4eLp6fnAz83mUwCQIKCgszb3nzzTXFzc5O9e/dKaWmprFixQpycnOTrr78WEZGVK1cKAPn888/l1q1bUlRUJGPHjhV3d3epqakREZGKigoxGAyyceNGqa6uluvXr8uUKVOkuLjYpjraC+ychyEpKUlcXV3lww8/lLKyMjl79qwMHTpUevfuLdevXzeXmzVrlvj5+Vnsm5KSIgDM5ygiEhMTI+Hh4Rbl4uLixN3dXc6dOye3b9+W3NxcGT58uOj1erly5Uq71HHo0CHR6/WSnJxs87k3as08I6QMe69vUgbnGekwnGeku9Dr9VCpVObFrm7fvo309HRER0cjJiYGXl5eWLVqFdRqNTIyMiz2jYyMhMFggI+PD2JjY1FZWYkrV64AAPLz82EymTBgwABoNBr4+flh37596N27t111dKbq6mqkpqZiypQpmD17Njw9PTFo0CDs2LEDN2/exM6dO9utLhcXF/Pdl/79+yM9PR3l5eXtdv5RUVEwmUxYvXp1uxyPiKgrYjLSTVRWVkJEYDAYAADnz59HVVUVBg4caC6j1Wrh7+9v8ajifq6urgCA2tpaAEBYWBh8fX0xe/ZsrFmzBvn5+eayra2jo+Xm5qKiosJqcazhw4fD1dXV4jFKexs2bBh0Op2i509E5GiYjHQTFy5cAAD069cPwN3kBABWrVplMT/J5cuXUVVVZfNxtVotjh07hjFjxmDdunUICwtDbGwsqqur262O9lZWVgYATa6y6uXl1eRS6e3Jzc3NvGooERG1jMlIN3H06FEAwIQJEwAAPj4+AIC0tDSr5bVPnDhh17EHDBiATz75BIWFhUhMTITRaMTmzZvbtY725OXlBQBNJh1lZWUIDAzssLpra2s7vA4iou6GyUg3cP36daSlpSEwMBAvv/wyACAoKAgajQZnzpxp07ELCwtx7tw5AHcTnHfeeQdDhw7FuXPn2q2O9jZw4EB4eHhYTQJ38uRJ1NTU4IknnjBvc3FxMT+Sag/Z2dkQEYwcObLD6iAi6m6YjDgQEUFFRQUaGhogIiguLobRaMTo0aPh7OyMAwcOmN8Z0Wg0eOmll7B7926kp6fDZDKhvr4eBQUF+PHHH22us7CwEPPnz8d3332HmpoanD59GpcvX8bIkSPbrY72ptFosGTJEuzfvx8fffQRTCYTcnJysGDBAgQEBCAuLs5cNiIiAj/99BMOHDiA2tpaFBcX4/Lly1bH7NWrFwoLC5Gfn4/y8nJzctHQ0IDS0lLU1dXh7NmzSEhIQHBwsHmodVvrOHLkCIf2ElH3p8wonu6rvYd+ffzxxzJ48GDR6XTi6uoqTk5OAkBUKpV4eXnJiBEjJDk5WUpKSqz2vXPnjiQmJkpwcLC4uLiIj4+PxMTESG5urmzfvl10Op0AkL59+0peXp7s3LlTDAaDAJCQkBC5cOGC5OfnS2RkpHh7e4uzs7M8/PDDsnLlSqmrq2uxjvYEO4c+NjQ0SEpKivTt21fUarV4e3tLdHS0nD9/3qJcSUmJPPXUU6LRaCQ0NFRef/11Wbp0qQCQiIgI8xDdU6dOSUhIiGi1WhkzZoxcv35d4uLiRK1WS58+fcTFxUUMBoNMnjxZ8vLy2q2Ow4cPi16vl7Vr19rdZhza6zjsvb5JGRza22EyVSIiimVC3VBmZiZmzJgBNmv7UqlUMBqNmD59utKhmM2fPx9ZWVkoKSlROpQmTZs2DQCQlZWlcCTUkq54fZM1fr93mCw+piFqg/r6eqVDICJyeExGiIiISFFMRohaYcWKFcjIyMCtW7cQGhqKvXv3Kh0SEZHDclE6ACJHtH79eqxfv17pMIiIugXeGSEiIiJFMRkhIiIiRTEZISIiIkUxGSEiIiJF8QXWDtI44RS1n7S0NE7gZYd//OMfAHgtOgpe311fQUGB0iF0W5yBtZ2dOHECqampSodBREQdhElju8tiMkJERERK4nTwREREpCwmI0RERKQoJiNERESkKCYjREREpKj/D9eToxoG7fXmAAAAAElFTkSuQmCC\n"
},
"metadata": {},
"execution_count": 62
}
]
},
{
"cell_type": "code",
"source": [
"EPOCHS = 50\n",
"#learning_rate = 1e-4\n",
"#decay_rate = learning_rate / EPOCHS\n",
"#opt = tf.optimizers.Adam(lr=learning_rate, beta_1=0.9, beta_2=0.999, epsilon=None, decay=decay_rate, amsgrad=False)\n",
"\n",
"Model.compile(optimizer = 'adam' , loss = 'categorical_crossentropy' , metrics = ['accuracy'])\n",
"\n",
"callbacks = [ModelCheckpoint('speech-emotion-recgonition.hdf5', verbose=1, save_best_only=True)]\n",
"\n",
"history = Model.fit(X_train, y_train,\n",
" batch_size=64,\n",
" epochs=EPOCHS, \n",
" callbacks=callbacks,\n",
" validation_data = (X_test, y_test))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "vgXSRpY3FTXQ",
"outputId": "62b9443e-4602-4a74-de51-b792ffdbdc64"
},
"execution_count": 66,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Epoch 1/50\n",
"119/119 [==============================] - ETA: 0s - loss: 2.0021 - accuracy: 0.3382\n",
"Epoch 1: val_loss improved from inf to 0.90804, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 52s 431ms/step - loss: 2.0021 - accuracy: 0.3382 - val_loss: 0.9080 - val_accuracy: 0.7643\n",
"Epoch 2/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.8971 - accuracy: 0.7001\n",
"Epoch 2: val_loss improved from 0.90804 to 0.34190, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 70s 585ms/step - loss: 0.8971 - accuracy: 0.7001 - val_loss: 0.3419 - val_accuracy: 0.9000\n",
"Epoch 3/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.5618 - accuracy: 0.8114\n",
"Epoch 3: val_loss improved from 0.34190 to 0.27352, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 56s 472ms/step - loss: 0.5618 - accuracy: 0.8114 - val_loss: 0.2735 - val_accuracy: 0.9119\n",
"Epoch 4/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.4174 - accuracy: 0.8636\n",
"Epoch 4: val_loss improved from 0.27352 to 0.16523, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 60s 504ms/step - loss: 0.4174 - accuracy: 0.8636 - val_loss: 0.1652 - val_accuracy: 0.9452\n",
"Epoch 5/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.3057 - accuracy: 0.9025\n",
"Epoch 5: val_loss improved from 0.16523 to 0.12444, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 51s 422ms/step - loss: 0.3057 - accuracy: 0.9025 - val_loss: 0.1244 - val_accuracy: 0.9667\n",
"Epoch 6/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.2450 - accuracy: 0.9185\n",
"Epoch 6: val_loss improved from 0.12444 to 0.11489, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 50s 424ms/step - loss: 0.2450 - accuracy: 0.9185 - val_loss: 0.1149 - val_accuracy: 0.9631\n",
"Epoch 7/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1901 - accuracy: 0.9351\n",
"Epoch 7: val_loss improved from 0.11489 to 0.11096, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 50s 417ms/step - loss: 0.1901 - accuracy: 0.9351 - val_loss: 0.1110 - val_accuracy: 0.9655\n",
"Epoch 8/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1812 - accuracy: 0.9411\n",
"Epoch 8: val_loss improved from 0.11096 to 0.07342, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 50s 421ms/step - loss: 0.1812 - accuracy: 0.9411 - val_loss: 0.0734 - val_accuracy: 0.9726\n",
"Epoch 9/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1553 - accuracy: 0.9484\n",
"Epoch 9: val_loss did not improve from 0.07342\n",
"119/119 [==============================] - 51s 430ms/step - loss: 0.1553 - accuracy: 0.9484 - val_loss: 0.0905 - val_accuracy: 0.9702\n",
"Epoch 10/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1535 - accuracy: 0.9504\n",
"Epoch 10: val_loss did not improve from 0.07342\n",
"119/119 [==============================] - 49s 407ms/step - loss: 0.1535 - accuracy: 0.9504 - val_loss: 0.0983 - val_accuracy: 0.9714\n",
"Epoch 11/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1195 - accuracy: 0.9624\n",
"Epoch 11: val_loss improved from 0.07342 to 0.06259, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 50s 418ms/step - loss: 0.1195 - accuracy: 0.9624 - val_loss: 0.0626 - val_accuracy: 0.9762\n",
"Epoch 12/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0920 - accuracy: 0.9681\n",
"Epoch 12: val_loss did not improve from 0.06259\n",
"119/119 [==============================] - 49s 408ms/step - loss: 0.0920 - accuracy: 0.9681 - val_loss: 0.0765 - val_accuracy: 0.9750\n",
"Epoch 13/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1027 - accuracy: 0.9671\n",
"Epoch 13: val_loss improved from 0.06259 to 0.06106, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 50s 417ms/step - loss: 0.1027 - accuracy: 0.9671 - val_loss: 0.0611 - val_accuracy: 0.9833\n",
"Epoch 14/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1107 - accuracy: 0.9626\n",
"Epoch 14: val_loss did not improve from 0.06106\n",
"119/119 [==============================] - 49s 410ms/step - loss: 0.1107 - accuracy: 0.9626 - val_loss: 0.0851 - val_accuracy: 0.9750\n",
"Epoch 15/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.1130 - accuracy: 0.9668\n",
"Epoch 15: val_loss improved from 0.06106 to 0.05039, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 50s 417ms/step - loss: 0.1130 - accuracy: 0.9668 - val_loss: 0.0504 - val_accuracy: 0.9750\n",
"Epoch 16/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0857 - accuracy: 0.9701\n",
"Epoch 16: val_loss did not improve from 0.05039\n",
"119/119 [==============================] - 48s 407ms/step - loss: 0.0857 - accuracy: 0.9701 - val_loss: 0.0609 - val_accuracy: 0.9786\n",
"Epoch 17/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0810 - accuracy: 0.9731\n",
"Epoch 17: val_loss improved from 0.05039 to 0.03221, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 49s 416ms/step - loss: 0.0810 - accuracy: 0.9731 - val_loss: 0.0322 - val_accuracy: 0.9893\n",
"Epoch 18/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0949 - accuracy: 0.9716\n",
"Epoch 18: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 49s 415ms/step - loss: 0.0949 - accuracy: 0.9716 - val_loss: 0.0636 - val_accuracy: 0.9810\n",
"Epoch 19/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0646 - accuracy: 0.9775\n",
"Epoch 19: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 48s 406ms/step - loss: 0.0646 - accuracy: 0.9775 - val_loss: 0.0359 - val_accuracy: 0.9881\n",
"Epoch 20/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0694 - accuracy: 0.9763\n",
"Epoch 20: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 50s 417ms/step - loss: 0.0694 - accuracy: 0.9763 - val_loss: 0.0987 - val_accuracy: 0.9798\n",
"Epoch 21/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0970 - accuracy: 0.9718\n",
"Epoch 21: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 48s 406ms/step - loss: 0.0970 - accuracy: 0.9718 - val_loss: 0.0707 - val_accuracy: 0.9786\n",
"Epoch 22/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0772 - accuracy: 0.9750\n",
"Epoch 22: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 50s 416ms/step - loss: 0.0772 - accuracy: 0.9750 - val_loss: 0.0389 - val_accuracy: 0.9833\n",
"Epoch 23/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0559 - accuracy: 0.9812\n",
"Epoch 23: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 48s 406ms/step - loss: 0.0559 - accuracy: 0.9812 - val_loss: 0.0508 - val_accuracy: 0.9845\n",
"Epoch 24/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0525 - accuracy: 0.9825\n",
"Epoch 24: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 49s 409ms/step - loss: 0.0525 - accuracy: 0.9825 - val_loss: 0.1285 - val_accuracy: 0.9714\n",
"Epoch 25/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0769 - accuracy: 0.9754\n",
"Epoch 25: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 48s 403ms/step - loss: 0.0769 - accuracy: 0.9754 - val_loss: 0.0703 - val_accuracy: 0.9786\n",
"Epoch 26/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0617 - accuracy: 0.9824\n",
"Epoch 26: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 48s 400ms/step - loss: 0.0617 - accuracy: 0.9824 - val_loss: 0.1064 - val_accuracy: 0.9726\n",
"Epoch 27/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0512 - accuracy: 0.9837\n",
"Epoch 27: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 49s 413ms/step - loss: 0.0512 - accuracy: 0.9837 - val_loss: 0.0620 - val_accuracy: 0.9821\n",
"Epoch 28/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0520 - accuracy: 0.9825\n",
"Epoch 28: val_loss did not improve from 0.03221\n",
"119/119 [==============================] - 48s 400ms/step - loss: 0.0520 - accuracy: 0.9825 - val_loss: 0.0347 - val_accuracy: 0.9881\n",
"Epoch 29/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0397 - accuracy: 0.9870\n",
"Epoch 29: val_loss improved from 0.03221 to 0.02746, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 49s 411ms/step - loss: 0.0397 - accuracy: 0.9870 - val_loss: 0.0275 - val_accuracy: 0.9893\n",
"Epoch 30/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0484 - accuracy: 0.9839\n",
"Epoch 30: val_loss improved from 0.02746 to 0.01914, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 48s 401ms/step - loss: 0.0484 - accuracy: 0.9839 - val_loss: 0.0191 - val_accuracy: 0.9893\n",
"Epoch 31/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0350 - accuracy: 0.9889\n",
"Epoch 31: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 49s 412ms/step - loss: 0.0350 - accuracy: 0.9889 - val_loss: 0.0347 - val_accuracy: 0.9893\n",
"Epoch 32/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0280 - accuracy: 0.9893\n",
"Epoch 32: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 48s 400ms/step - loss: 0.0280 - accuracy: 0.9893 - val_loss: 0.0522 - val_accuracy: 0.9857\n",
"Epoch 33/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0508 - accuracy: 0.9849\n",
"Epoch 33: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 49s 410ms/step - loss: 0.0508 - accuracy: 0.9849 - val_loss: 0.0400 - val_accuracy: 0.9881\n",
"Epoch 34/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0456 - accuracy: 0.9848\n",
"Epoch 34: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 47s 398ms/step - loss: 0.0456 - accuracy: 0.9848 - val_loss: 0.1066 - val_accuracy: 0.9810\n",
"Epoch 35/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0720 - accuracy: 0.9790\n",
"Epoch 35: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 49s 409ms/step - loss: 0.0720 - accuracy: 0.9790 - val_loss: 0.0255 - val_accuracy: 0.9905\n",
"Epoch 36/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0528 - accuracy: 0.9825\n",
"Epoch 36: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 49s 408ms/step - loss: 0.0528 - accuracy: 0.9825 - val_loss: 0.1220 - val_accuracy: 0.9726\n",
"Epoch 37/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0353 - accuracy: 0.9873\n",
"Epoch 37: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 48s 400ms/step - loss: 0.0353 - accuracy: 0.9873 - val_loss: 0.0357 - val_accuracy: 0.9940\n",
"Epoch 38/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0468 - accuracy: 0.9851\n",
"Epoch 38: val_loss did not improve from 0.01914\n",
"119/119 [==============================] - 49s 411ms/step - loss: 0.0468 - accuracy: 0.9851 - val_loss: 0.0430 - val_accuracy: 0.9869\n",
"Epoch 39/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0320 - accuracy: 0.9892\n",
"Epoch 39: val_loss improved from 0.01914 to 0.01846, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 48s 401ms/step - loss: 0.0320 - accuracy: 0.9892 - val_loss: 0.0185 - val_accuracy: 0.9940\n",
"Epoch 40/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0233 - accuracy: 0.9919\n",
"Epoch 40: val_loss did not improve from 0.01846\n",
"119/119 [==============================] - 49s 410ms/step - loss: 0.0233 - accuracy: 0.9919 - val_loss: 0.0412 - val_accuracy: 0.9833\n",
"Epoch 41/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0397 - accuracy: 0.9882\n",
"Epoch 41: val_loss did not improve from 0.01846\n",
"119/119 [==============================] - 47s 398ms/step - loss: 0.0397 - accuracy: 0.9882 - val_loss: 0.0327 - val_accuracy: 0.9893\n",
"Epoch 42/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0470 - accuracy: 0.9861\n",
"Epoch 42: val_loss did not improve from 0.01846\n",
"119/119 [==============================] - 61s 517ms/step - loss: 0.0470 - accuracy: 0.9861 - val_loss: 0.0730 - val_accuracy: 0.9881\n",
"Epoch 43/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0453 - accuracy: 0.9868\n",
"Epoch 43: val_loss did not improve from 0.01846\n",
"119/119 [==============================] - 53s 446ms/step - loss: 0.0453 - accuracy: 0.9868 - val_loss: 0.0655 - val_accuracy: 0.9845\n",
"Epoch 44/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0289 - accuracy: 0.9906\n",
"Epoch 44: val_loss did not improve from 0.01846\n",
"119/119 [==============================] - 54s 451ms/step - loss: 0.0289 - accuracy: 0.9906 - val_loss: 0.0208 - val_accuracy: 0.9929\n",
"Epoch 45/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0327 - accuracy: 0.9901\n",
"Epoch 45: val_loss did not improve from 0.01846\n",
"119/119 [==============================] - 48s 407ms/step - loss: 0.0327 - accuracy: 0.9901 - val_loss: 0.0425 - val_accuracy: 0.9881\n",
"Epoch 46/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0304 - accuracy: 0.9914\n",
"Epoch 46: val_loss improved from 0.01846 to 0.01836, saving model to speech-emotion-recgonition.hdf5\n",
"119/119 [==============================] - 48s 405ms/step - loss: 0.0304 - accuracy: 0.9914 - val_loss: 0.0184 - val_accuracy: 0.9929\n",
"Epoch 47/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0312 - accuracy: 0.9911\n",
"Epoch 47: val_loss did not improve from 0.01836\n",
"119/119 [==============================] - 48s 406ms/step - loss: 0.0312 - accuracy: 0.9911 - val_loss: 0.0225 - val_accuracy: 0.9929\n",
"Epoch 48/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0282 - accuracy: 0.9906\n",
"Epoch 48: val_loss did not improve from 0.01836\n",
"119/119 [==============================] - 48s 404ms/step - loss: 0.0282 - accuracy: 0.9906 - val_loss: 0.0288 - val_accuracy: 0.9893\n",
"Epoch 49/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0299 - accuracy: 0.9906\n",
"Epoch 49: val_loss did not improve from 0.01836\n",
"119/119 [==============================] - 48s 407ms/step - loss: 0.0299 - accuracy: 0.9906 - val_loss: 0.0722 - val_accuracy: 0.9857\n",
"Epoch 50/50\n",
"119/119 [==============================] - ETA: 0s - loss: 0.0497 - accuracy: 0.9858\n",
"Epoch 50: val_loss did not improve from 0.01836\n",
"119/119 [==============================] - 48s 405ms/step - loss: 0.0497 - accuracy: 0.9858 - val_loss: 0.0209 - val_accuracy: 0.9917\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"#-----------------------------------------------------------\n",
"# Retrieve a list of list results on train and test data\n",
"# sets for each training epoch\n",
"#-----------------------------------------------------------\n",
"acc = history.history['accuracy']\n",
"val_acc = history.history['val_accuracy']\n",
"loss = history.history['loss']\n",
"val_loss = history.history['val_loss']\n",
"\n",
"epochs = range(len(acc)) # Get number of epochs\n",
"\n",
"#------------------------------------------------\n",
"# Plot training and test accuracy per epoch\n",
"#------------------------------------------------\n",
"plt.figure(figsize=(15,5))\n",
"plt.plot (epochs, acc, 'bo', color = '#ff0066')\n",
"plt.plot (epochs, val_acc, color = '#00ccff')\n",
"plt.title ('Train and Test Accuracy')\n",
"plt.legend(['train', 'test'], loc='upper left')\n",
"plt.ylabel('dice coef')\n",
"plt.xlabel('epoch');\n",
"\n",
"#------------------------------------------------\n",
"# Plot training and test loss per epoch\n",
"#------------------------------------------------\n",
"plt.figure(figsize=(15,5))\n",
"plt.plot (epochs, loss, 'bo', color = '#ff0066')\n",
"plt.plot (epochs, val_loss, color = '#00ccff')\n",
"plt.legend(['train', 'test'], loc='upper right')\n",
"plt.ylabel('loss')\n",
"plt.xlabel('epoch')\n",
"plt.title ('Training and Validation Loss');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 683
},
"id": "YcLisklSGPyw",
"outputId": "098265bc-d14f-4e99-a0fa-709702b5fc8e"
},
"execution_count": 67,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1080x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 1080x360 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"model = load_model('speech-emotion-recgonition.hdf5')"
],
"metadata": {
"id": "c4jjl0C4N4wi"
},
"execution_count": 70,
"outputs": []
},
{
"cell_type": "code",
"source": [
"results = model.evaluate(X_test, y_test)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "l7rwkdjUORzh",
"outputId": "2c2fc5bc-7ac7-442f-a2b9-e8794e4d6046"
},
"execution_count": 72,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"27/27 [==============================] - 2s 70ms/step - loss: 0.0184 - accuracy: 0.9929\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print('Test loss: ', results[0])\n",
"print('Test Acuuracy: ', results[1])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Sl-GYm6MRAhL",
"outputId": "a5d3f68d-ee3f-480a-aa4c-a09b36d08a2e"
},
"execution_count": 73,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Test loss: 0.018359793350100517\n",
"Test Acuuracy: 0.9928571581840515\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"prediction_test = Model.predict(X_test)\n",
"y_prediction = encoder_label.inverse_transform(prediction_test)\n",
"\n",
"y_test = encoder_label.inverse_transform(y_test)"
],
"metadata": {
"id": "bgbZAD5VUx1v"
},
"execution_count": 76,
"outputs": []
},
{
"cell_type": "code",
"source": [
"print(prediction_test[0:10])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "JCnXeyOyU2Vc",
"outputId": "d4fdfee1-f7fa-47b9-c658-7629c03bf40c"
},
"execution_count": 75,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[[1.2539381e-35 2.6577417e-25 1.0000000e+00 8.2832591e-27 7.3499556e-14\n",
" 7.7953851e-22 8.5821120e-17 0.0000000e+00 1.0052549e-23 6.5280599e-38\n",
" 0.0000000e+00 1.8144091e-31 7.1360247e-24 1.7140523e-15]\n",
" [2.3596723e-33 1.7425503e-18 2.3295285e-28 2.4711690e-27 3.2881669e-23\n",
" 5.1089242e-23 6.4766343e-25 7.9290117e-18 1.7867358e-16 1.3654086e-17\n",
" 2.5968544e-28 1.5442032e-25 1.0000000e+00 6.4055432e-20]\n",
" [1.0000000e+00 8.0895154e-22 3.4732483e-38 2.5107539e-20 3.3402157e-23\n",
" 5.3391074e-26 1.0854162e-28 4.1783998e-29 3.5626304e-32 5.0885492e-27\n",
" 1.1747909e-24 1.0154011e-26 8.8076060e-33 1.1067026e-34]\n",
" [1.8798333e-16 2.9010328e-16 2.3319381e-13 1.2988915e-18 7.1985068e-14\n",
" 9.7448682e-23 1.0000000e+00 9.0837906e-26 3.6552545e-22 3.0899621e-22\n",
" 1.0979684e-27 1.6812562e-14 9.6981158e-13 2.8822607e-22]\n",
" [2.3574526e-16 1.0000000e+00 1.7059810e-25 2.5045686e-17 2.2699506e-10\n",
" 1.8099232e-08 6.8503353e-22 2.1773176e-18 2.2160013e-14 7.4349589e-19\n",
" 2.6823290e-25 1.4266034e-24 6.5437879e-13 1.8723222e-20]\n",
" [3.0259796e-12 3.5308483e-05 1.8118940e-10 1.2834103e-09 7.4141821e-07\n",
" 9.9996400e-01 1.0003536e-14 3.7363785e-16 8.8303225e-13 1.4533132e-12\n",
" 2.1284858e-16 2.8435186e-15 4.9022737e-11 6.4256706e-10]\n",
" [4.6422737e-18 6.8589050e-24 1.3814552e-26 9.8985063e-25 1.3901304e-18\n",
" 4.4002539e-31 6.7141622e-18 8.4398349e-27 2.6168432e-20 4.4045642e-26\n",
" 2.9742700e-33 1.0000000e+00 4.8994890e-29 2.8366012e-22]\n",
" [4.0488853e-22 1.2341448e-27 9.1811188e-35 6.5418677e-24 1.7224746e-23\n",
" 3.1479538e-35 1.0920554e-24 1.9007195e-27 2.1901935e-28 8.9328200e-29\n",
" 2.8489435e-36 1.0000000e+00 4.2272072e-34 9.2321323e-31]\n",
" [1.0000000e+00 7.2187027e-11 1.2745564e-25 8.5897518e-15 9.6142331e-15\n",
" 1.4530618e-14 8.7898456e-19 3.0403242e-17 5.4980962e-17 1.5926339e-15\n",
" 2.7084355e-17 1.7700658e-18 1.6653938e-18 1.8074135e-21]\n",
" [8.3514515e-12 9.9987912e-01 5.8546203e-17 4.4290296e-13 7.3946886e-08\n",
" 1.1843028e-04 3.4090641e-15 2.8616672e-11 2.4390443e-08 4.1264714e-11\n",
" 3.4122610e-17 7.2685088e-17 2.2645049e-06 3.5979763e-12]]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(y_prediction[0:10])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "QLr4OyCkU5_z",
"outputId": "05675727-fc39-4375-9b2b-488dfc4a75fc"
},
"execution_count": 77,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[['OAF_Sad']\n",
" ['YAF_pleasant_surprised']\n",
" ['OAF_Fear']\n",
" ['OAF_neutral']\n",
" ['OAF_Pleasant_surprise']\n",
" ['OAF_happy']\n",
" ['YAF_neutral']\n",
" ['YAF_neutral']\n",
" ['OAF_Fear']\n",
" ['OAF_Pleasant_surprise']]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"print(y_test[0:10])"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "6EdDEShAU-w6",
"outputId": "07e64149-5b65-465b-d65a-e2f90c0b7ba6"
},
"execution_count": 78,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"[['OAF_Sad']\n",
" ['YAF_pleasant_surprised']\n",
" ['OAF_Fear']\n",
" ['OAF_neutral']\n",
" ['OAF_Pleasant_surprise']\n",
" ['OAF_happy']\n",
" ['YAF_neutral']\n",
" ['YAF_neutral']\n",
" ['OAF_Fear']\n",
" ['OAF_Pleasant_surprise']]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"conf_matrix = confusion_matrix(y_test, y_prediction)\n",
"\n",
"plt.figure(figsize=(13,6))\n",
"sns.heatmap(conf_matrix, linecolor='white', cmap='Blues', linewidth=1, annot=True, fmt='')\n",
"\n",
"plt.title('Confusion Matrix')\n",
"plt.xlabel('Predicted Labels')\n",
"plt.ylabel('Actual Labels');"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 404
},
"id": "GimCY4YsVE4O",
"outputId": "79b3a6d8-0565-47f4-f20f-34d89f80f2f9"
},
"execution_count": 80,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 936x432 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"print(classification_report(y_test, y_prediction))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "MmQxD4xrVhI0",
"outputId": "2992d24f-45e8-421e-981c-19d30858c8aa"
},
"execution_count": 81,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
" precision recall f1-score support\n",
"\n",
" OAF_Fear 1.00 1.00 1.00 74\n",
" OAF_Pleasant_surprise 1.00 0.98 0.99 59\n",
" OAF_Sad 1.00 0.97 0.99 76\n",
" OAF_angry 1.00 0.98 0.99 56\n",
" OAF_disgust 0.96 1.00 0.98 46\n",
" OAF_happy 0.99 1.00 0.99 70\n",
" OAF_neutral 1.00 1.00 1.00 50\n",
" YAF_angry 1.00 1.00 1.00 65\n",
" YAF_disgust 0.96 1.00 0.98 51\n",
" YAF_fear 1.00 1.00 1.00 51\n",
" YAF_happy 1.00 1.00 1.00 57\n",
" YAF_neutral 1.00 1.00 1.00 57\n",
"YAF_pleasant_surprised 1.00 0.95 0.98 64\n",
" YAF_sad 0.97 1.00 0.98 64\n",
"\n",
" accuracy 0.99 840\n",
" macro avg 0.99 0.99 0.99 840\n",
" weighted avg 0.99 0.99 0.99 840\n",
"\n"
]
}
]
}
]
}