{ "metadata": { "name": "", "signature": "sha256:10a96a42f1a86ec36e94c4b4752dae6f748916ce4faf6c29f6cfae3032f5f073" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Using Audio in IPython" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Audio Libraries" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will mainly use three libraries for audio acquisition and playback: `IPython.display.Audio`, `essentia.standard`, and `librosa`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Introduced in IPython 2.0, [`IPython.display.Audio`](http://ipython.org/ipython-doc/2/api/generated/IPython.lib.display.html#IPython.lib.display.Audio) lets you play audio directly in an IPython notebook." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[Essentia](http://essentia.upf.edu) is an open-source library for audio analysis and music information retrieval \n", "from the [Music Technology Group at Universitat Pompeu Fabra](http://mtg.upf.edu/home). \n", "Although Essentia is written in C++, we will use the Python bindings for Essentia.\n", "\n", "- [Documentation Home](http://essentia.upf.edu/documentation/)\n", "- [Python Tutorial](http://essentia.upf.edu/documentation/python_tutorial.html)\n", "- [Essentia on GitHub](https://github.com/MTG/essentia)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`librosa` is a Python package for music and audio processing by [Brian McFee](http://cosmal.ucsd.edu/~bmcfee/). A large portion was ported from [Dan Ellis's Matlab audio processing examples](http://www.ee.columbia.edu/%7Edpwe/resources/matlab/).\n", "\n", "- [Documentation Home](http://bmcfee.github.io/librosa/)\n", "- [Demo: Getting Started](http://nbviewer.ipython.org/github/bmcfee/librosa/blob/master/examples/LibROSA%20demo.ipynb)\n", "- [librosa on Github](https://github.com/bmcfee/librosa/)" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Retrieving Audio" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To download a file onto your local machine (or Vagrant box) in Python, you can use `urllib.urlretrieve`:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import urllib\n", "urllib.urlretrieve('https://ccrma.stanford.edu/workshops/mir2014/audio/simpleLoop.wav', filename='simpleLoop.wav')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 1, "text": [ "('simpleLoop.wav', )" ] } ], "prompt_number": 1 }, { "cell_type": "markdown", "metadata": {}, "source": [ "To check that the file downloaded successfully, list the files in the working directory:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "%ls *.wav" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\u001b[0m\u001b[00;36mdefault.wav\u001b[0m \u001b[00;36mout.wav\u001b[0m \u001b[00;36msimpleLoop.wav\u001b[0m\r\n" ] } ], "prompt_number": 2 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visit https://ccrma.stanford.edu/workshops/mir2014/audio/ for more audio files." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you only want to listen to, and not manipulate, a remote audio file, use `IPython.display.Audio` instead. (See [Playing Audio](#Playing-Audio).)" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Reading Audio" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "`essentia.standard.Monoloader`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[`MonoLoader`](http://essentia.upf.edu/documentation/reference/std_MonoLoader.html) reads (and downmixes, if necessary) an audio file into a single channel (as will often be the case during this workshop). `MonoLoader` also resamples the audio to a sampling frequency of your choice (default = 44100 Hz):" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from essentia.standard import MonoLoader\n", "audio = MonoLoader(filename='simpleLoop.wav')()\n", "audio.shape" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 3, "text": [ "(132300,)" ] } ], "prompt_number": 3 }, { "cell_type": "code", "collapsed": false, "input": [ "N = len(audio)\n", "t = arange(0, N)/44100.0\n", "plot(t, audio)\n", "xlabel('Time (seconds)')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 4, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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ychZPnz79PedLnEvr1hHV1RFZrVayWq1EhOAH90h5UTgAtSguLqbi4mKvl+My\n+NPS0orq6+sHOr7+0ksv/cH+Z5PJxEwmk9OI3rp166iwsLBjx48fH5CWllYUGxu7PzU1dcuVc86l\niROJpk27/FUEv/qpYRtJ1eJXw7oBCPaNYiKiefPmebQcl8FfVFSU1tHvQkNDG+rr6wcOHDiw/tix\nY2HXXHPNv53NFxYWdoyIaMCAAccnT568uqysbKTz4DdGV4/e1kct0NUD4D6PPyZZWVl5S5cuzSYi\nWrp0afakSZPWOM7T2NgYdP78+T5ERBcvXuy1YcOGsfHx8bs7Wia+pmuTq52ZXNsUB3cB3Ofxx2T2\n7NkLioqK0mJiYg5+/fXXt8+ePXsBEdHRo0cHZWZm5hMR1dfXD0xNTd2SlJRUmZKSUjp+/Ph/jh07\ndkNHyzRCi99IBg2S77wMqVr8aIyAHnl8cLd///6nNm7ceIfj64MGDTqan5+fSUT0i1/84qfKysok\nd5fp7EOLD576dbRzrquTrzy5TuAC0ANVfTF2FvIIfnAH+vgB3Keqj4kRgl+PLUi510npq3MCaJ2q\nrtXjGPIff0zUrZsydQFtQfADuE/Vwf/II8rUA7pGDd9iAgMvn0rhwAHplg0gJ1W1j/TWrQPyCQoi\nGjBA2lsvits8Amgdgh+8poY+/oAAon87PYUQABwh+GUUHEz06qtK1wIAjE5Vwa/3A3O33MK7I/RG\nDX38AOA+VUWt3lv8AABqgOAHr+m5xa/ndQPjUlXwA7gDYQzgHQQ/eE0No3oAwH0IfhmhKwsA1ADB\nD15DCxxAWxD8MkKLX3uwUwM9UlXwIxi1yQjh+PjjStcAwHdUFfx6N3260jXQByV2NO+9J3+ZAFJB\n8MtkzBiiCROUroU0jNDiB9ATBL9M0I2lTdipgR4h+MFrGMcPoC0IfvAaghhAWxD8Mhk6VOkaAABw\nqrr1ol41NUl7S0CloasHQFtUFfx6PQDao4fSNQBPYduBHqGrB7ym5xZ4z576Xj8wJgQ/AIDBIPjB\na2vWKF0DAOgKBD947fBhpWsAAF2hquAPUNWhZlAr9LkDeEdVwe/vr3QNwBMTJ8pbHoIfwDsIfvDa\n++8TbdyodC0AwF0IfvDa1Vfzq48CgDYg+AEADAbBDwBgMAh+0Bwc3AXwjsfB/8UXX9w7bNiwPf7+\n/m3l5eXJHc1XWFh4Z2xs7P7o6OiqhQsXPu9qmQh+cAeCH8A7Hgd/fHz87tWrV08ePXr05o7maWtr\n8585c2YnHe3TAAAOHklEQVRuYWHhnXv37h26bNmyB/bt2xfX0fyRkZ7WBoykvV3pGgBom8enTMXG\nxu7vbJ6ysrKRUVFRhyIjI6uJiKZMmbJ87dq1E+Pi4vY5zotWHLirrU3pGgBom6TnytbV1YWbzeYa\n8XNERERtaWlpirN5586d+9/nVquVrFarlFUDDUOLH4yquLiYiouLvV6Oy+BPS0srqq+vH+j4+ssv\nv/y/EyZMWNfZwk0mk9vtePvgB3DllVeI9u5VuhYA8nNsFM+bN8+j5bgM/qKiojSPlvof4eHhdTU1\nNWbxc01NjTkiIqLWm2UCjB7NHwDgGZ8M52SMOb131ogRI3ZUVVVFV1dXRzY3N3dbsWLF/VlZWXm+\nKBMAADzjcfCvXr16stlsrikpKbkpMzMzPyMjYz0R0dGjRwdlZmbmExEFBAS05ubmzkxPT/9y6NCh\ne++///4Vzg7sAgCAfExMBcNpTCYTU0M9AAC0xGQyddjj4oqqztwFAADpIfgBAAwGwQ8AYDAIfgAA\ng0HwAwAYDIIfAMBgEPwAAAaD4AcAMBgEPwCAwSD4AQAMBsEPAGAwCH4AAINB8AMAGAyCHwDAYBD8\nAAAGg+AHADAYBD8AgMEg+AEADAbBDwBgMAh+AACDQfADABgMgh8AwGAQ/AAABoPgBwAwGAQ/AIDB\nIPgBAAwGwQ8AYDAIfgAAg0HwAwAYDIIfAMBgEPwAAAaD4AcAMBgEPwCAwSD4AQAMBsEPAGAwCH4Z\nFBcXK10Fyeh53Yiwflqn9/XzlMfB/8UXX9w7bNiwPf7+/m3l5eXJHc0XGRlZnZCQsMtisVSMHDmy\nzNPytEzPbz49rxsR1k/r9L5+ngrw9A/j4+N3r169enJOTs5iV/OZTCZWXFxs7d+//ylPywIAAN/x\nOPhjY2P3uzsvY8zkaTkAAOBjjDGvHlarddP333+f3NHvBw8e/FNSUlLFDTfcsOPdd9+d7mweImJ4\n4IEHHnh0/eFJbrts8aelpRXV19cPdHz95Zdf/t8JEyasc/W3wtatW0eFhYUdO378+IC0tLSi2NjY\n/ampqVvs58E3AgAA+bgM/qKiojRvCwgLCztGRDRgwIDjkydPXl1WVjbSMfgBAEA+PhnO2VGLvbGx\nMej8+fN9iIguXrzYa8OGDWPj4+N3+6JMAADwjMfBv3r16slms7mmpKTkpszMzPyMjIz1RERHjx4d\nlJmZmU9EVF9fPzA1NXVLUlJSZUpKSun48eP/OXbs2A2+qjwAAHjA24O7XXmsX7/+ziFDhuyPioqq\nWrBgwfPO5vnNb37zRlRUVFVCQsLO8vJyi5z1k3r9Nm3aZO3bt+/ZpKSkiqSkpIr58+e/oHSd3X08\n9thjH15zzTUNw4cP393RPFredp2tn5a33ZEjR8xWq3XT0KFD9wwbNuyH119/fZaetp8766fl7dfU\n1NRj5MiRpYmJiZVxcXF7Z8+e/Rdvt59slW9tbfW//vrrDx0+fDiyubk5MDExsXLv3r1x9vPk5+eP\ny8jIKGCMUUlJSUpKSkqJ0v90X67fpk2brBMmTMhTuq6ePDZv3pxaXl5u6SgYtbzt3Fk/LW+7Y8eO\nDayoqEhijNH58+d7x8TEHNDTZ8+d9dPy9mOM0cWLF4MYY9TS0hKQkpJSsmXLllu82X6yXbKhrKxs\nZFRU1KHIyMjqwMDAlilTpixfu3btRPt58vLysrKzs5cSEaWkpJSeOXOmX0NDQ6hcdfSGO+tHpN0R\nTKmpqVtCQkJOd/R7LW87os7Xj0i7227gwIH1SUlJlUREvXv3vhAXF7fv6NGjg+zn0fL2c2f9iLS7\n/YiIgoKCGomImpubu7W1tfk7nhDb1e0nW/DX1dWFm83mGvFzREREbV1dXXhn89TW1kbIVUdvuLN+\nJpOJbdu27ZeJiYk7x40bV7B3796h8tdUGlredu7Qy7arrq6OrKiosKSkpJTav66X7dfR+ml9+7W3\nt/slJSVVhoaGNtx2222bhg4dutf+913dfh6fudtVJpOJuTOf417Z3b9Tmjv1TE5OLq+pqTEHBQU1\nrl+/PmPSpElrDh48GCNH/eSg1W3nDj1suwsXLvS+5557Vr7++utP9e7d+4Lj77W+/Vytn9a3n5+f\nX3tlZWXS2bNng9PT078sLi62Wq3WYvt5urL9ZGvxh4eH19XU1JjFzzU1NeaIiIhaV/PU1tZGhIeH\n18lVR2+4s359+vQ5L76yZWRkrG9paQk8depUf7nrKgUtbzt3aH3btbS0BN59993/ePjhhz+ZNGnS\nGsffa337dbZ+Wt9+QnBw8NnMzMz8HTt2jLB/vavbT7bgHzFixI6qqqro6urqyObm5m4rVqy4Pysr\nK89+nqysrLyPP/74USKikpKSm/r163cmNDS0Qa46esOd9WtoaAgVe+WysrKRjDGTXi5ep+Vt5w4t\nbzvGmGnatGkfDB06dO9vf/vb15zNo+Xt5876aXn7nThx4uozZ870IyJqamrqWVRUlGaxWCrs5+ny\n9pPzyHRBQUFGTEzMgeuvv/7Qyy+//HvGGL3zzjs577zzTo6Y58knn8y9/vrrDyUkJOx0dQ0gNT46\nW7/c3Nwnhw0b9kNiYmLlzTffvG379u03KV1ndx9TpkxZFhYWdjQwMLA5IiKi5oMPPpiqp23X2fpp\nedtt2bLlFpPJ1J6YmFgphjMWFBRk6GX7ubN+Wt5+u3btirdYLOWJiYmV8fHxu1555ZXnGPMuO02M\naaobDwAAvIQ7cAEAGAyCHwDAYBD8AAAGg+AHADAYBD+oxsmTJ6+yWCwVFoulIiws7FhEREStxWKp\n6NOnz/mZM2fmSlFmbm7uzI8++uhXUizbE5GRkdWuxpffd999nx8+fHiwnHUC/cGoHlClefPmzenT\np8/5Z5555lWpymCMmZKTk8u/++67GwMCAlqlKqcrBg8efPj777+/oaMx5kVFRWnr1q2b8MYbb8yS\nu26gH2jxg2qx/5xwU1xcbBW3+pw7d+7c7OzspaNHj94cGRlZvWrVqrueffbZRQkJCbsyMjLWt7a2\nBhARff/99zdYrdbiESNG7LjzzjsLnd1CdOvWraNiY2P3i9B/4403Zg0bNmxPYmLizgceeGAZEb+B\n0NSpUz9MSUkpTU5OLs/Ly8siImpra/N/9tlnF8XHx+9OTEzcmZubO5OI6KuvvhqTnJxcnpCQsGva\ntGkfNDc3dyPiLfm5c+fOveGGG75PSEjYdeDAgSFE/FvO2LFjNwwfPvyH6dOnvyfW+eLFi70yMzPz\nk5KSKuPj43d//vnn9xERWa3W4oKCgnHS/udB95Q+OQEPPJw95s6dO2fRokW/Y4xfUnf8+PHrGGM0\nZ86cuampqZtbW1v9d+7cmdCzZ8/GwsLCdMYYTZ48edWaNWsmNjc3B958883bTpw4cRVjjJYvX37/\n1KlTP3As4y9/+ctsUQZjjAYNGlTX3NwcyBijs2fP9mWM0e9///uXP/nkk4cYY3T69Ol+MTExBy5e\nvBj01ltvzbj33ns/b2tr82OM0alTp0Kampp6mM3mI1VVVVGMMXr00UeXvvbaa08xxigyMvJwbm7u\nk4wxeuutt2Y8/vjj7zHGr6E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"text": [ "" ] } ], "prompt_number": 4 }, { "cell_type": "markdown", "metadata": {}, "source": [ "For more control over the audio acquisition process, you may want to use [`AudioLoader`](http://essentia.upf.edu/documentation/reference/std_AudioLoader.html) instead." ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "`librosa.load`" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import librosa\n", "x, fs = librosa.load('simpleLoop.wav')\n", "print x.shape\n", "print fs" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "(66150,)\n", "22050\n" ] } ], "prompt_number": 5 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Playing Audio" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "`IPython.display.Audio`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using [`IPython.display.Audio`](http://ipython.org/ipython-doc/2/api/generated/IPython.lib.display.html#IPython.lib.display.Audio), you can play a local audio file or a remote audio file:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "from IPython.display import Audio\n", "Audio('https://ccrma.stanford.edu/workshops/mir2014/audio/CongaGroove-mono.wav') # remote WAV file" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 6, "text": [ "" ] } ], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "Audio('simpleLoop.wav') # local WAV file" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 7, "text": [ "" ] } ], "prompt_number": 7 }, { "cell_type": "markdown", "metadata": {}, "source": [ "`Audio` can also accept a NumPy array:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "fs = 44100 # sampling frequency\n", "T = 1.5 # seconds\n", "t = numpy.linspace(0, T, int(T*fs), endpoint=False) # time variable\n", "x = numpy.sin(2*numpy.pi*440*t) # pure sine wave at 440 Hz\n", "Audio(x, rate=fs)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "\n", " \n", " " ], "metadata": {}, "output_type": "pyout", "prompt_number": 8, "text": [ "" ] } ], "prompt_number": 8 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "SoX" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To play audio from the command line, we recommend SoX (included in the `stanford-mir` Vagrant box).\n", "\n", " $ play simpleLoop.wav" ] }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Visualizing Audio" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`plot` is the simplest way to plot time-domain signals:" ] }, { "cell_type": "code", "collapsed": false, "input": [ "T = 0.001 # seconds\n", "fs = 44100 # sampling frequency\n", "t = numpy.linspace(0, T, int(T*fs), endpoint=False) # time variable\n", "x = numpy.sin(2*numpy.pi*3000*t) \n", "plot(t, x)\n", "xlabel('Time (seconds)')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 9, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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NoEG8LeEPZTJZDgkEJ0ggtIvBoD03E7mXbkMuJsshgeBEVBRz2WgFk4ndEMnF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\n62LhQraUrLnlZFtb2cx+8mT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"text": [ "" ] } ], "prompt_number": 9 }, { "cell_type": "markdown", "metadata": {}, "source": [ "`specgram` is a Matplotlib tool for computing and displaying spectrograms." ] }, { "cell_type": "code", "collapsed": true, "input": [ "S, freqs, bins, im = specgram(x, NFFT=1024, Fs=fs, noverlap=512)\n", "xlabel('Time')\n", "ylabel('Frequency')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ "" ] }, { "metadata": {}, "output_type": "display_data", "png": 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"text": [ "" ] } ], "prompt_number": 10 }, { "cell_type": "heading", "level": 2, "metadata": {}, "source": [ "Writing Audio" ] }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "`essentia.standard.MonoWriter`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[`MonoWriter`](http://essentia.upf.edu/documentation/reference/std_MonoWriter.html) can write a NumPy array to a WAV file. Note: the array must have type `int`, `single`, or `complex64`." ] }, { "cell_type": "code", "collapsed": false, "input": [ "from essentia.standard import MonoWriter\n", "noise = 0.1*randn(44100)\n", "MonoWriter(filename='noise1.wav')(single(noise))\n", "%ls *.wav" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\u001b[0m\u001b[00;36mdefault.wav\u001b[0m \u001b[00;36mnoise1.wav\u001b[0m \u001b[00;36mout.wav\u001b[0m \u001b[00;36msimpleLoop.wav\u001b[0m\r\n" ] } ], "prompt_number": 11 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "`librosa.output.write_wav`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`librosa.output.write_wav` also saves a NumPy array to a WAV file. This is a bit easier to use." ] }, { "cell_type": "code", "collapsed": false, "input": [ "import librosa\n", "noise = 0.1*randn(44100)\n", "librosa.output.write_wav('noise2.wav', noise, 44100)\n", "%ls *.wav" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "\u001b[0m\u001b[00;36mdefault.wav\u001b[0m \u001b[00;36mnoise1.wav\u001b[0m \u001b[00;36mnoise2.wav\u001b[0m \u001b[00;36mout.wav\u001b[0m \u001b[00;36msimpleLoop.wav\u001b[0m\r\n" ] } ], "prompt_number": 12 } ], "metadata": {} } ] }