{"cells":[{"cell_type":"markdown","metadata":{},"source":["# Text to Speech\n","> Generating synthetic voice from the given text using open-source TTS models.\n","\n","- toc: false\n","- badges: true\n","- comments: true\n","- categories: [tts, audio]"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{},"colab_type":"code","id":"EXiuKtGYe1wl"},"outputs":[],"source":["TEXT = \"hello homosapien, I am a synthetic voice created by Sparsh\""]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"JtT8cQjmeTqW"},"source":["## Tacotron2 + WaveGlow"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":85},"colab_type":"code","executionInfo":{"elapsed":22315,"status":"ok","timestamp":1587669507724,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"XQdE5JIUk3r5","outputId":"59a2a454-24a9-4e8f-990a-07a5dabfc473"},"outputs":[{"name":"stdout","output_type":"stream","text":["TensorFlow 1.x selected.\n","Previous HEAD position was 4b1001f Merge branch 'master' of https://github.com/NVIDIA/waveglow\n","HEAD is now at 9168aea README.md: layout\n","\u001b[K |████████████████████████████████| 245kB 2.8MB/s \n","\u001b[?25h"]}],"source":["%tensorflow_version 1.x\n","import os\n","from os.path import exists, join, basename, splitext\n","\n","git_repo_url = 'https://github.com/NVIDIA/tacotron2.git'\n","project_name = splitext(basename(git_repo_url))[0]\n","if not exists(project_name):\n"," # clone and install\n"," !git clone -q --recursive {git_repo_url}\n"," !cd {project_name}/waveglow && git checkout 9168aea\n"," !pip install -q librosa unidecode\n"," \n","import sys\n","sys.path.append(join(project_name, 'waveglow/'))\n","sys.path.append(project_name)\n","import time\n","import matplotlib\n","import matplotlib.pylab as plt\n","plt.rcParams[\"axes.grid\"] = False"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":221},"colab_type":"code","executionInfo":{"elapsed":62285,"status":"ok","timestamp":1587669547701,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"jXLnnH9zeZb6","outputId":"d2d86d74-1c8e-407f-e0db-83cda780a259"},"outputs":[{"name":"stdout","output_type":"stream","text":[" % Total % Received % Xferd Average Speed Time Time Time Current\n"," Dload Upload Total Spent Left Speed\n","\r 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r100 408 0 408 0 0 1012 0 --:--:-- --:--:-- --:--:-- 1014\n"," 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n"," 0 0 0 0 0 0 0 0 --:--:-- 0:00:01 --:--:-- 0\n","100 107M 0 107M 0 0 24.1M 0 --:--:-- 0:00:04 --:--:-- 58.8M\n"," % Total % Received % Xferd Average Speed Time Time Time Current\n"," Dload Upload Total Spent Left Speed\n","100 408 0 408 0 0 1030 0 --:--:-- --:--:-- --:--:-- 1027\n"," 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n"," 0 0 0 0 0 0 0 0 --:--:-- 0:00:01 --:--:-- 0\n","100 644M 0 644M 0 0 58.1M 0 --:--:-- 0:00:11 --:--:-- 83.1M\n"]}],"source":["def download_from_google_drive(file_id, file_name):\n"," # download a file from the Google Drive link\n"," !rm -f ./cookie\n"," !curl -c ./cookie -s -L \"https://drive.google.com/uc?export=download&id={file_id}\" > /dev/null\n"," confirm_text = !awk '/download/ {print $NF}' ./cookie\n"," confirm_text = confirm_text[0]\n"," !curl -Lb ./cookie \"https://drive.google.com/uc?export=download&confirm={confirm_text}&id={file_id}\" -o {file_name}\n","\n","tacotron2_pretrained_model = 'tacotron2_statedict.pt'\n","if not exists(tacotron2_pretrained_model):\n"," # download the Tacotron2 pretrained model\n"," download_from_google_drive('1c5ZTuT7J08wLUoVZ2KkUs_VdZuJ86ZqA', tacotron2_pretrained_model)\n","waveglow_pretrained_model = 'waveglow_old.pt'\n","if not exists(waveglow_pretrained_model):\n"," # download the Waveglow pretrained model \n"," download_from_google_drive('1WsibBTsuRg_SF2Z6L6NFRTT-NjEy1oTx', waveglow_pretrained_model)"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":309},"colab_type":"code","executionInfo":{"elapsed":90000,"status":"ok","timestamp":1587669576163,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"sGzgsTsgea06","outputId":"0785c82d-9e34-4f5f-c828-cabc72379477"},"outputs":[{"name":"stdout","output_type":"stream","text":["WARNING:tensorflow:\n","The TensorFlow contrib module will not be included in TensorFlow 2.0.\n","For more information, please see:\n"," * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n"," * https://github.com/tensorflow/addons\n"," * https://github.com/tensorflow/io (for I/O related ops)\n","If you depend on functionality not listed there, please file an issue.\n","\n"]},{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/torch/serialization.py:593: SourceChangeWarning: source code of class 'torch.nn.modules.conv.ConvTranspose1d' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n"," warnings.warn(msg, SourceChangeWarning)\n","/usr/local/lib/python3.6/dist-packages/torch/serialization.py:593: SourceChangeWarning: source code of class 'torch.nn.modules.container.ModuleList' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n"," warnings.warn(msg, SourceChangeWarning)\n","/usr/local/lib/python3.6/dist-packages/torch/serialization.py:593: SourceChangeWarning: source code of class 'torch.nn.modules.conv.Conv1d' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n"," warnings.warn(msg, SourceChangeWarning)\n","/usr/local/lib/python3.6/dist-packages/torch/serialization.py:593: SourceChangeWarning: source code of class 'glow.Invertible1x1Conv' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n"," warnings.warn(msg, SourceChangeWarning)\n"]}],"source":["import IPython.display as ipd\n","import numpy as np\n","import torch\n","\n","from hparams import create_hparams\n","from model import Tacotron2\n","from layers import TacotronSTFT\n","from audio_processing import griffin_lim\n","from text import text_to_sequence\n","from denoiser import Denoiser\n","\n","def plot_data(data, figsize=(16, 4)):\n"," fig, axes = plt.subplots(1, len(data), figsize=figsize)\n"," for i in range(len(data)):\n"," axes[i].imshow(data[i], aspect='auto', origin='bottom', \n"," interpolation='none', cmap='viridis')\n","\n","torch.set_grad_enabled(False)\n"," \n","# initialize Tacotron2 with the pretrained model\n","hparams = create_hparams()\n","hparams.sampling_rate = 22050\n","model = Tacotron2(hparams)\n","model.load_state_dict(torch.load(tacotron2_pretrained_model)['state_dict'])\n","_ = model.cuda().eval()#.half()\n","\n","# initialize Waveglow with the pretrained model\n","# waveglow = torch.load(waveglow_pretrained_model)['model']\n","# WORKAROUND for: https://github.com/NVIDIA/tacotron2/issues/182\n","import json\n","from glow import WaveGlow\n","waveglow_config = json.load(open('%s/waveglow/config.json' % project_name))['waveglow_config']\n","waveglow = WaveGlow(**waveglow_config)\n","waveglow.load_state_dict(torch.load(waveglow_pretrained_model)['model'].state_dict())\n","_ = waveglow.cuda().eval()#.half()\n","for k in waveglow.convinv:\n"," k.float()\n","denoiser = Denoiser(waveglow)"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":265},"colab_type":"code","executionInfo":{"elapsed":4560,"status":"ok","timestamp":1587669602232,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"okc_vkk0ecoS","outputId":"c4669ea0-4ac8-4d4f-dde7-5533c33aafe0"},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{"needs_background":"light","tags":[]},"output_type":"display_data"}],"source":["sequence = np.array(text_to_sequence(TEXT, ['english_cleaners']))[None, :]\n","sequence = torch.autograd.Variable(torch.from_numpy(sequence)).long()\n","sequence = sequence.cuda()\n","\n","mel_outputs, mel_outputs_postnet, _, alignments = model.inference(sequence)\n","plot_data((mel_outputs.data.cpu().numpy()[0],\n"," mel_outputs_postnet.data.cpu().numpy()[0],\n"," alignments.data.cpu().numpy()[0].T))"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":75},"colab_type":"code","executionInfo":{"elapsed":3072,"status":"ok","timestamp":1587669606497,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"EWCfCJ1Ne32W","outputId":"e8f9bfa4-4f8a-4f48-bb6c-da5157bd64e9"},"outputs":[{"data":{"text/html":["\n"," \n"," "],"text/plain":[""]},"execution_count":6,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["audio = waveglow.infer(mel_outputs_postnet, sigma=0.666)\n","ipd.Audio(audio[0].data.cpu().numpy(), rate=hparams.sampling_rate)"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":75},"colab_type":"code","executionInfo":{"elapsed":3006,"status":"ok","timestamp":1587669612413,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"ZmuZsnqFe5Qe","outputId":"00151118-d719-4328-971e-65b9fdafc623"},"outputs":[{"data":{"text/html":["\n"," \n"," "],"text/plain":[""]},"execution_count":7,"metadata":{"tags":[]},"output_type":"execute_result"}],"source":["# remove waveglow bias\n","audio_denoised = denoiser(audio, strength=0.01)[:, 0]\n","ipd.Audio(audio_denoised.cpu().numpy(), rate=hparams.sampling_rate)"]},{"cell_type":"markdown","metadata":{"colab_type":"text","id":"I3VZTK8Wh_Xx"},"source":["## ESPnet real time E2E-TTS demonstration\n","\n","This notebook provides a demonstration of the realtime E2E-TTS using ESPnet-TTS and ParallelWaveGAN (+ MelGAN).\n","\n","- ESPnet: https://github.com/espnet/espnet\n","- ParallelWaveGAN: https://github.com/kan-bayashi/ParallelWaveGAN"]},{"cell_type":"code","execution_count":9,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":187},"colab_type":"code","executionInfo":{"elapsed":31114,"status":"ok","timestamp":1587670986808,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"0cUJji_HhT4b","outputId":"6c527994-93e3-4877-ad88-17cb5ef1b998"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[K |████████████████████████████████| 51kB 8.7MB/s \n","\u001b[K |████████████████████████████████| 3.1MB 39.5MB/s \n","\u001b[K |████████████████████████████████| 1.6MB 48.5MB/s \n","\u001b[K |████████████████████████████████| 184kB 62.2MB/s \n","\u001b[?25h Building wheel for parallel-wavegan (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Building wheel for ConfigArgparse (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Building wheel for librosa (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Building wheel for kaldiio (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Building wheel for distance (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Switched to a new branch 'v.0.6.1'\n"]}],"source":["# install minimal components\n","!pip install -q parallel_wavegan PyYaml unidecode ConfigArgparse g2p_en nltk\n","!git clone -q https://github.com/espnet/espnet.git\n","!cd espnet && git fetch && git checkout -b v.0.6.1 1e8b6ce88d57b53d1b60cbb3f306652468b0ab63"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":561},"colab_type":"code","executionInfo":{"elapsed":42135,"status":"ok","timestamp":1587670998066,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"ztWZjy_XOPZR","outputId":"4a81572d-0455-4e41-a489-c1eb78774fad"},"outputs":[{"name":"stdout","output_type":"stream","text":["--2020-04-23 19:43:07-- https://drive.google.com/uc?export=download&id=1z8KSOWVBjK-_Ws4RxVN4NTx-Buy03-7c\n","Resolving drive.google.com (drive.google.com)... 172.217.4.174, 2607:f8b0:4007:803::200e\n","Connecting to drive.google.com (drive.google.com)|172.217.4.174|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: unspecified [text/html]\n","Saving to: ‘downloads/en/transformer/EJmpGT.tar.gz’\n","\n","\r downloads [<=> ] 0 --.-KB/s \rdownloads/en/transf [ <=> ] 3.23K --.-KB/s in 0s \n","\n","2020-04-23 19:43:07 (23.9 MB/s) - ‘downloads/en/transformer/EJmpGT.tar.gz’ saved [3305]\n","\n","\n","gzip: stdin: not in gzip format\n","tar: Child returned status 1\n","tar: Error is not recoverable: exiting now\n"," % Total % Received % Xferd Average Speed Time Time Time Current\n"," Dload Upload Total Spent Left Speed\n","\r 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r100 3305 0 3305 0 0 8956 0 --:--:-- --:--:-- --:--:-- 8956\n"," % Total % Received % Xferd Average Speed Time Time Time Current\n"," Dload Upload Total Spent Left Speed\n","100 408 0 408 0 0 971 0 --:--:-- --:--:-- --:--:-- 969\n"," 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n"," 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\n","100 117M 0 117M 0 0 17.9M 0 --:--:-- 0:00:06 --:--:-- 22.8M\n","conf/tuning/train_pytorch_transformer.v3.single.yaml\n","conf/decode.yaml\n","data/phn_train_no_dev/cmvn.ark\n","exp/phn_train_no_dev_pytorch_train_pytorch_transformer.v3.single/results/model.last1.avg.best\n","exp/phn_train_no_dev_pytorch_train_pytorch_transformer.v3.single/results/model.json\n","data/lang_1phn/phn_train_no_dev_units.txt\n","Sucessfully downloaded zip file from https://drive.google.com/open?id=1z8KSOWVBjK-_Ws4RxVN4NTx-Buy03-7c\n","sucessfully finished download.\n"]}],"source":["# download pretrained model\n","import os\n","if not os.path.exists(\"downloads/en/transformer\"):\n"," !./espnet/utils/download_from_google_drive.sh \\\n"," https://drive.google.com/open?id=1z8KSOWVBjK-_Ws4RxVN4NTx-Buy03-7c downloads/en/transformer tar.gz\n","\n","# set path\n","trans_type = \"phn\"\n","dict_path = \"downloads/en/transformer/data/lang_1phn/phn_train_no_dev_units.txt\"\n","model_path = \"downloads/en/transformer/exp/phn_train_no_dev_pytorch_train_pytorch_transformer.v3.single/results/model.last1.avg.best\"\n","\n","print(\"sucessfully finished download.\")"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":428},"colab_type":"code","executionInfo":{"elapsed":47258,"status":"ok","timestamp":1587671003450,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"nQDFNuQ2dK-M","outputId":"d7085533-24ea-4cc9-f499-efebab6414bd"},"outputs":[{"name":"stdout","output_type":"stream","text":["--2020-04-23 19:43:18-- https://drive.google.com/uc?export=download&id=1Grn7X9wD35UcDJ5F7chwdTqTa4U7DeVB\n","Resolving drive.google.com (drive.google.com)... 172.217.14.78, 2607:f8b0:4007:801::200e\n","Connecting to drive.google.com (drive.google.com)|172.217.14.78|:443... connected.\n","HTTP request sent, awaiting response... 302 Moved Temporarily\n","Location: https://doc-0o-30-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/6i824otlc8vf6svrn5ibifrvff194os3/1587670950000/04214513489132088126/*/1Grn7X9wD35UcDJ5F7chwdTqTa4U7DeVB?e=download [following]\n","Warning: wildcards not supported in HTTP.\n","--2020-04-23 19:43:20-- https://doc-0o-30-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/6i824otlc8vf6svrn5ibifrvff194os3/1587670950000/04214513489132088126/*/1Grn7X9wD35UcDJ5F7chwdTqTa4U7DeVB?e=download\n","Resolving doc-0o-30-docs.googleusercontent.com (doc-0o-30-docs.googleusercontent.com)... 172.217.14.97, 2607:f8b0:4007:80e::2001\n","Connecting to doc-0o-30-docs.googleusercontent.com (doc-0o-30-docs.googleusercontent.com)|172.217.14.97|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: unspecified [application/x-gzip]\n","Saving to: ‘downloads/en/parallel_wavegan/s6swvM.tar.gz’\n","\n","downloads/en/parall [ <=> ] 15.23M 34.7MB/s in 0.4s \n","\n","2020-04-23 19:43:21 (34.7 MB/s) - ‘downloads/en/parallel_wavegan/s6swvM.tar.gz’ saved [15975388]\n","\n","ljspeech.parallel_wavegan.v2/\n","ljspeech.parallel_wavegan.v2/stats.h5\n","ljspeech.parallel_wavegan.v2/checkpoint-400000steps.pkl\n","ljspeech.parallel_wavegan.v2/config.yml\n","Sucessfully downloaded zip file from https://drive.google.com/open?id=1Grn7X9wD35UcDJ5F7chwdTqTa4U7DeVB\n","Sucessfully finished download.\n"]}],"source":["# download pretrained model\n","import os\n","if not os.path.exists(\"downloads/en/parallel_wavegan\"):\n"," !./espnet/utils/download_from_google_drive.sh \\\n"," https://drive.google.com/open?id=1Grn7X9wD35UcDJ5F7chwdTqTa4U7DeVB downloads/en/parallel_wavegan tar.gz\n","\n","# set path\n","vocoder_path = \"downloads/en/parallel_wavegan/ljspeech.parallel_wavegan.v2/checkpoint-400000steps.pkl\"\n","vocoder_conf = \"downloads/en/parallel_wavegan/ljspeech.parallel_wavegan.v2/config.yml\"\n","\n","print(\"Sucessfully finished download.\")"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":187},"colab_type":"code","executionInfo":{"elapsed":61212,"status":"ok","timestamp":1587671017940,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"i8JXOfRfqMFN","outputId":"115517a8-d1fc-4dab-a3fe-e5950e1af87b"},"outputs":[{"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/chainer/_environment_check.py:77: UserWarning: Failed to check requirement: cupy-cuda101>=6.5.0,<7.0.0\n"," 'Failed to check requirement: {}'.format(requirement))\n"]},{"name":"stdout","output_type":"stream","text":["[nltk_data] Downloading package averaged_perceptron_tagger to\n","[nltk_data] /root/nltk_data...\n","[nltk_data] Unzipping taggers/averaged_perceptron_tagger.zip.\n","[nltk_data] Downloading package cmudict to /root/nltk_data...\n","[nltk_data] Unzipping corpora/cmudict.zip.\n","[nltk_data] Downloading package punkt to /root/nltk_data...\n","[nltk_data] Unzipping tokenizers/punkt.zip.\n","Now ready to synthesize!\n"]}],"source":["# add path\n","import sys\n","sys.path.append(\"espnet/egs/ljspeech/tts1/local\")\n","sys.path.append(\"espnet\")\n","\n","# define device\n","import torch\n","device = torch.device(\"cuda\")\n","\n","# define E2E-TTS model\n","from argparse import Namespace\n","from espnet.asr.asr_utils import get_model_conf\n","from espnet.asr.asr_utils import torch_load\n","from espnet.utils.dynamic_import import dynamic_import\n","idim, odim, train_args = get_model_conf(model_path)\n","model_class = dynamic_import(train_args.model_module)\n","model = model_class(idim, odim, train_args)\n","torch_load(model_path, model)\n","model = model.eval().to(device)\n","inference_args = Namespace(**{\n"," \"threshold\": 0.5,\"minlenratio\": 0.0, \"maxlenratio\": 10.0,\n"," \"use_attention_constraint\": True,\n"," \"backward_window\": 1, \"forward_window\":3,\n"," })\n","\n","# define neural vocoder\n","import yaml\n","import parallel_wavegan.models\n","with open(vocoder_conf) as f:\n"," config = yaml.load(f, Loader=yaml.Loader)\n","vocoder_class = config.get(\"generator_type\", \"ParallelWaveGANGenerator\")\n","vocoder = getattr(parallel_wavegan.models, vocoder_class)(**config[\"generator_params\"])\n","vocoder.load_state_dict(torch.load(vocoder_path, map_location=\"cpu\")[\"model\"][\"generator\"])\n","vocoder.remove_weight_norm()\n","vocoder = vocoder.eval().to(device)\n","\n","# define text frontend\n","from text.cleaners import custom_english_cleaners\n","from g2p_en import G2p\n","with open(dict_path) as f:\n"," lines = f.readlines()\n","lines = [line.replace(\"\\n\", \"\").split(\" \") for line in lines]\n","char_to_id = {c: int(i) for c, i in lines}\n","g2p = G2p()\n","def frontend(text):\n"," \"\"\"Clean text and then convert to id sequence.\"\"\"\n"," text = custom_english_cleaners(text)\n"," \n"," if trans_type == \"phn\":\n"," text = filter(lambda s: s != \" \", g2p(text))\n"," text = \" \".join(text)\n"," print(f\"Cleaned text: {text}\")\n"," charseq = text.split(\" \")\n"," else:\n"," print(f\"Cleaned text: {text}\")\n"," charseq = list(text)\n"," idseq = []\n"," for c in charseq:\n"," if c.isspace():\n"," idseq += [char_to_id[\"\"]]\n"," elif c not in char_to_id.keys():\n"," idseq += [char_to_id[\"\"]]\n"," else:\n"," idseq += [char_to_id[c]]\n"," idseq += [idim - 1] # \n"," return torch.LongTensor(idseq).view(-1).to(device)\n","\n","import nltk\n","nltk.download('punkt')\n","print(\"Now ready to synthesize!\")"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":143},"colab_type":"code","executionInfo":{"elapsed":103982,"status":"ok","timestamp":1587671061890,"user":{"displayName":"Sparsh Agarwal","photoUrl":"","userId":"13037694610922482904"},"user_tz":-330},"id":"9gGRzrjyudWF","outputId":"5b54332c-e25b-4923-af7d-d44c8074dbf9"},"outputs":[{"name":"stdout","output_type":"stream","text":["Input your favorite sentence in English!\n","hello homosapien, I am a synthetic voice created by Sparsh\n","Cleaned text: HH AH0 L OW1 HH OW0 M OW0 S EY1 P IY0 AH0 N , AY1 AE1 M AH0 S IH0 N TH EH1 T IH0 K V OY1 S K R IY0 EY1 T AH0 D B AY1 S P AA1 R SH\n","RTF = 0.904254\n"]},{"data":{"text/html":["\n"," \n"," "],"text/plain":[""]},"metadata":{"tags":[]},"output_type":"display_data"}],"source":["import time\n","print(\"Input your favorite sentence in English!\")\n","input_text = input()\n","pad_fn = torch.nn.ReplicationPad1d(\n"," config[\"generator_params\"].get(\"aux_context_window\", 0))\n","use_noise_input = vocoder_class == \"ParallelWaveGANGenerator\"\n","with torch.no_grad():\n"," start = time.time()\n"," x = frontend(input_text)\n"," c, _, _ = model.inference(x, inference_args)\n"," c = pad_fn(c.unsqueeze(0).transpose(2, 1)).to(device)\n"," xx = (c,)\n"," if use_noise_input:\n"," z_size = (1, 1, (c.size(2) - sum(pad_fn.padding)) * config[\"hop_size\"])\n"," z = torch.randn(z_size).to(device)\n"," xx = (z,) + xx\n"," y = vocoder(*xx).view(-1)\n","rtf = (time.time() - start) / (len(y) / config[\"sampling_rate\"])\n","print(f\"RTF = {rtf:5f}\")\n","\n","from IPython.display import display, Audio\n","display(Audio(y.view(-1).cpu().numpy(), rate=config[\"sampling_rate\"]))"]}],"metadata":{"accelerator":"GPU","colab":{"authorship_tag":"ABX9TyN1fMxRYRqEDusG1MQMHnC6","collapsed_sections":[],"name":"1a699a67-13e1-48ee-b94a-8d22d34d0bb6","provenance":[]},"kernelspec":{"display_name":"Python 3","name":"python3"}},"nbformat":4,"nbformat_minor":0}