music_IRMAS_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "from scipy.stats import norm\n",
    "import pandas as pd\n",
    "\n",
    "from models.VAE import VariationalAutoencoder\n",
    "from utils.loaders import load_model\n",
    "\n",
    "%matplotlib inline\n",
    "import IPython.display\n",
    "from ipywidgets import interact, interactive, fixed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Packages we're using\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import copy\n",
    "from scipy.io import wavfile\n",
    "from scipy.signal import butter, lfilter\n",
    "import scipy.ndimage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.environ['TF_FORCE_GPU_ALLOW_GROWTH'] = 'true'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Most of the Spectrograms and Inversion are taken from: https://gist.github.com/kastnerkyle/179d6e9a88202ab0a2fe\n",
    "\n",
    "\n",
    "def butter_bandpass(lowcut, highcut, fs, order=5):\n",
    "    nyq = 0.5 * fs\n",
    "    low = lowcut / nyq\n",
    "    high = highcut / nyq\n",
    "    b, a = butter(order, [low, high], btype=\"band\")\n",
    "    return b, a\n",
    "\n",
    "\n",
    "def butter_bandpass_filter(data, lowcut, highcut, fs, order=5):\n",
    "    b, a = butter_bandpass(lowcut, highcut, fs, order=order)\n",
    "    y = lfilter(b, a, data)\n",
    "    return y\n",
    "\n",
    "\n",
    "def overlap(X, window_size, window_step):\n",
    "    \"\"\"\n",
    "    Create an overlapped version of X\n",
    "    Parameters\n",
    "    ----------\n",
    "    X : ndarray, shape=(n_samples,)\n",
    "        Input signal to window and overlap\n",
    "    window_size : int\n",
    "        Size of windows to take\n",
    "    window_step : int\n",
    "        Step size between windows\n",
    "    Returns\n",
    "    -------\n",
    "    X_strided : shape=(n_windows, window_size)\n",
    "        2D array of overlapped X\n",
    "    \"\"\"\n",
    "    if window_size % 2 != 0:\n",
    "        raise ValueError(\"Window size must be even!\")\n",
    "    # Make sure there are an even number of windows before stridetricks\n",
    "    append = np.zeros((window_size - len(X) % window_size))\n",
    "    X = np.hstack((X, append))\n",
    "\n",
    "    ws = window_size\n",
    "    ss = window_step\n",
    "    a = X\n",
    "\n",
    "    valid = len(a) - ws\n",
    "    nw = (valid) // ss\n",
    "    out = np.ndarray((nw, ws), dtype=a.dtype)\n",
    "\n",
    "    for i in np.arange(nw):\n",
    "        # \"slide\" the window along the samples\n",
    "        start = i * ss\n",
    "        stop = start + ws\n",
    "        out[i] = a[start:stop]\n",
    "\n",
    "    return out\n",
    "\n",
    "\n",
    "def stft(\n",
    "    X, fftsize=128, step=65, mean_normalize=True, real=False, compute_onesided=True\n",
    "):\n",
    "    \"\"\"\n",
    "    Compute STFT for 1D real valued input X\n",
    "    \"\"\"\n",
    "    if real:\n",
    "        local_fft = np.fft.rfft\n",
    "        cut = -1\n",
    "    else:\n",
    "        local_fft = np.fft.fft\n",
    "        cut = None\n",
    "    if compute_onesided:\n",
    "        cut = fftsize // 2\n",
    "    if mean_normalize:\n",
    "        X -= X.mean()\n",
    "\n",
    "    X = overlap(X, fftsize, step)\n",
    "\n",
    "    size = fftsize\n",
    "    win = 0.54 - 0.46 * np.cos(2 * np.pi * np.arange(size) / (size - 1))\n",
    "    X = X * win[None]\n",
    "    X = local_fft(X)[:, :cut]\n",
    "    return X\n",
    "\n",
    "\n",
    "def pretty_spectrogram(d, log=True, thresh=5, fft_size=512, step_size=64):\n",
    "    \"\"\"\n",
    "    creates a spectrogram\n",
    "    log: take the log of the spectrgram\n",
    "    thresh: threshold minimum power for log spectrogram\n",
    "    \"\"\"\n",
    "    specgram = np.abs(\n",
    "        stft(d, fftsize=fft_size, step=step_size, real=False, compute_onesided=True)\n",
    "    )\n",
    "\n",
    "    if log == True:\n",
    "        specgram /= specgram.max()  # volume normalize to max 1\n",
    "        specgram = np.log10(specgram)  # take log\n",
    "        specgram[\n",
    "            specgram < -thresh\n",
    "        ] = -thresh  # set anything less than the threshold as the threshold\n",
    "    else:\n",
    "        specgram[\n",
    "            specgram < thresh\n",
    "        ] = thresh  # set anything less than the threshold as the threshold\n",
    "\n",
    "    return specgram\n",
    "\n",
    "\n",
    "# Also mostly modified or taken from https://gist.github.com/kastnerkyle/179d6e9a88202ab0a2fe\n",
    "def invert_pretty_spectrogram(\n",
    "    X_s, log=True, fft_size=512, step_size=512 / 4, n_iter=10\n",
    "):\n",
    "\n",
    "    if log == True:\n",
    "        X_s = np.power(10, X_s)\n",
    "\n",
    "    X_s = np.concatenate([X_s, X_s[:, ::-1]], axis=1)\n",
    "    X_t = iterate_invert_spectrogram(X_s, fft_size, step_size, n_iter=n_iter)\n",
    "    return X_t\n",
    "\n",
    "\n",
    "def iterate_invert_spectrogram(X_s, fftsize, step, n_iter=10, verbose=False):\n",
    "    \"\"\"\n",
    "    Under MSR-LA License\n",
    "    Based on MATLAB implementation from Spectrogram Inversion Toolbox\n",
    "    References\n",
    "    ----------\n",
    "    D. Griffin and J. Lim. Signal estimation from modified\n",
    "    short-time Fourier transform. IEEE Trans. Acoust. Speech\n",
    "    Signal Process., 32(2):236-243, 1984.\n",
    "    Malcolm Slaney, Daniel Naar and Richard F. Lyon. Auditory\n",
    "    Model Inversion for Sound Separation. Proc. IEEE-ICASSP,\n",
    "    Adelaide, 1994, II.77-80.\n",
    "    Xinglei Zhu, G. Beauregard, L. Wyse. Real-Time Signal\n",
    "    Estimation from Modified Short-Time Fourier Transform\n",
    "    Magnitude Spectra. IEEE Transactions on Audio Speech and\n",
    "    Language Processing, 08/2007.\n",
    "    \"\"\"\n",
    "    reg = np.max(X_s) / 1e8\n",
    "    X_best = copy.deepcopy(X_s)\n",
    "    for i in range(n_iter):\n",
    "        if verbose:\n",
    "            print(\"Runnning iter %i\" % i)\n",
    "        if i == 0:\n",
    "            X_t = invert_spectrogram(\n",
    "                X_best, step, calculate_offset=True, set_zero_phase=True\n",
    "            )\n",
    "        else:\n",
    "            # Calculate offset was False in the MATLAB version\n",
    "            # but in mine it massively improves the result\n",
    "            # Possible bug in my impl?\n",
    "            X_t = invert_spectrogram(\n",
    "                X_best, step, calculate_offset=True, set_zero_phase=False\n",
    "            )\n",
    "        est = stft(X_t, fftsize=fftsize, step=step, compute_onesided=False)\n",
    "        phase = est / np.maximum(reg, np.abs(est))\n",
    "        X_best = X_s * phase[: len(X_s)]\n",
    "    X_t = invert_spectrogram(X_best, step, calculate_offset=True, set_zero_phase=False)\n",
    "    return np.real(X_t)\n",
    "\n",
    "\n",
    "def invert_spectrogram(X_s, step, calculate_offset=True, set_zero_phase=True):\n",
    "    \"\"\"\n",
    "    Under MSR-LA License\n",
    "    Based on MATLAB implementation from Spectrogram Inversion Toolbox\n",
    "    References\n",
    "    ----------\n",
    "    D. Griffin and J. Lim. Signal estimation from modified\n",
    "    short-time Fourier transform. IEEE Trans. Acoust. Speech\n",
    "    Signal Process., 32(2):236-243, 1984.\n",
    "    Malcolm Slaney, Daniel Naar and Richard F. Lyon. Auditory\n",
    "    Model Inversion for Sound Separation. Proc. IEEE-ICASSP,\n",
    "    Adelaide, 1994, II.77-80.\n",
    "    Xinglei Zhu, G. Beauregard, L. Wyse. Real-Time Signal\n",
    "    Estimation from Modified Short-Time Fourier Transform\n",
    "    Magnitude Spectra. IEEE Transactions on Audio Speech and\n",
    "    Language Processing, 08/2007.\n",
    "    \"\"\"\n",
    "    size = int(X_s.shape[1] // 2)\n",
    "    wave = np.zeros((X_s.shape[0] * step + size))\n",
    "    # Getting overflow warnings with 32 bit...\n",
    "    wave = wave.astype(\"float64\")\n",
    "    total_windowing_sum = np.zeros((X_s.shape[0] * step + size))\n",
    "    win = 0.54 - 0.46 * np.cos(2 * np.pi * np.arange(size) / (size - 1))\n",
    "\n",
    "    est_start = int(size // 2) - 1\n",
    "    est_end = est_start + size\n",
    "    for i in range(X_s.shape[0]):\n",
    "        wave_start = int(step * i)\n",
    "        wave_end = wave_start + size\n",
    "        if set_zero_phase:\n",
    "            spectral_slice = X_s[i].real + 0j\n",
    "        else:\n",
    "            # already complex\n",
    "            spectral_slice = X_s[i]\n",
    "\n",
    "        # Don't need fftshift due to different impl.\n",
    "        wave_est = np.real(np.fft.ifft(spectral_slice))[::-1]\n",
    "        if calculate_offset and i > 0:\n",
    "            offset_size = size - step\n",
    "            if offset_size <= 0:\n",
    "                print(\n",
    "                    \"WARNING: Large step size >50\\% detected! \"\n",
    "                    \"This code works best with high overlap - try \"\n",
    "                    \"with 75% or greater\"\n",
    "                )\n",
    "                offset_size = step\n",
    "            offset = xcorr_offset(\n",
    "                wave[wave_start : wave_start + offset_size],\n",
    "                wave_est[est_start : est_start + offset_size],\n",
    "            )\n",
    "        else:\n",
    "            offset = 0\n",
    "        wave[wave_start:wave_end] += (\n",
    "            win * wave_est[est_start - offset : est_end - offset]\n",
    "        )\n",
    "        total_windowing_sum[wave_start:wave_end] += win\n",
    "    wave = np.real(wave) / (total_windowing_sum + 1e-6)\n",
    "    return wave\n",
    "\n",
    "\n",
    "def xcorr_offset(x1, x2):\n",
    "    \"\"\"\n",
    "    Under MSR-LA License\n",
    "    Based on MATLAB implementation from Spectrogram Inversion Toolbox\n",
    "    References\n",
    "    ----------\n",
    "    D. Griffin and J. Lim. Signal estimation from modified\n",
    "    short-time Fourier transform. IEEE Trans. Acoust. Speech\n",
    "    Signal Process., 32(2):236-243, 1984.\n",
    "    Malcolm Slaney, Daniel Naar and Richard F. Lyon. Auditory\n",
    "    Model Inversion for Sound Separation. Proc. IEEE-ICASSP,\n",
    "    Adelaide, 1994, II.77-80.\n",
    "    Xinglei Zhu, G. Beauregard, L. Wyse. Real-Time Signal\n",
    "    Estimation from Modified Short-Time Fourier Transform\n",
    "    Magnitude Spectra. IEEE Transactions on Audio Speech and\n",
    "    Language Processing, 08/2007.\n",
    "    \"\"\"\n",
    "    x1 = x1 - x1.mean()\n",
    "    x2 = x2 - x2.mean()\n",
    "    frame_size = len(x2)\n",
    "    half = frame_size // 2\n",
    "    corrs = np.convolve(x1.astype(\"float32\"), x2[::-1].astype(\"float32\"))\n",
    "    corrs[:half] = -1e30\n",
    "    corrs[-half:] = -1e30\n",
    "    offset = corrs.argmax() - len(x1)\n",
    "    return offset\n",
    "\n",
    "\n",
    "def make_mel(spectrogram, mel_filter, shorten_factor=1):\n",
    "    mel_spec = np.transpose(mel_filter).dot(np.transpose(spectrogram))\n",
    "    mel_spec = scipy.ndimage.zoom(\n",
    "        mel_spec.astype(\"float32\"), [1, 1.0 / shorten_factor]\n",
    "    ).astype(\"float16\")\n",
    "    mel_spec = mel_spec[:, 1:-1]  # a little hacky but seemingly needed for clipping\n",
    "    return mel_spec\n",
    "\n",
    "\n",
    "def mel_to_spectrogram(mel_spec, mel_inversion_filter, spec_thresh, shorten_factor):\n",
    "    \"\"\"\n",
    "    takes in an mel spectrogram and returns a normal spectrogram for inversion \n",
    "    \"\"\"\n",
    "    mel_spec = mel_spec + spec_thresh\n",
    "    uncompressed_spec = np.transpose(np.transpose(mel_spec).dot(mel_inversion_filter))\n",
    "    uncompressed_spec = scipy.ndimage.zoom(\n",
    "        uncompressed_spec.astype(\"float32\"), [1, shorten_factor]\n",
    "    ).astype(\"float16\")\n",
    "    uncompressed_spec = uncompressed_spec - 4\n",
    "    return uncompressed_spec\n",
    "\n",
    "\n",
    "# From https://github.com/jameslyons/python_speech_features\n",
    "\n",
    "\n",
    "def hz2mel(hz):\n",
    "    \"\"\"Convert a value in Hertz to Mels\n",
    "    :param hz: a value in Hz. This can also be a numpy array, conversion proceeds element-wise.\n",
    "    :returns: a value in Mels. If an array was passed in, an identical sized array is returned.\n",
    "    \"\"\"\n",
    "    return 2595 * np.log10(1 + hz / 700.0)\n",
    "\n",
    "\n",
    "def mel2hz(mel):\n",
    "    \"\"\"Convert a value in Mels to Hertz\n",
    "    :param mel: a value in Mels. This can also be a numpy array, conversion proceeds element-wise.\n",
    "    :returns: a value in Hertz. If an array was passed in, an identical sized array is returned.\n",
    "    \"\"\"\n",
    "    return 700 * (10 ** (mel / 2595.0) - 1)\n",
    "\n",
    "\n",
    "def get_filterbanks(nfilt=20, nfft=512, samplerate=16000, lowfreq=0, highfreq=None):\n",
    "    \"\"\"Compute a Mel-filterbank. The filters are stored in the rows, the columns correspond\n",
    "    to fft bins. The filters are returned as an array of size nfilt * (nfft/2 + 1)\n",
    "    :param nfilt: the number of filters in the filterbank, default 20.\n",
    "    :param nfft: the FFT size. Default is 512.\n",
    "    :param samplerate: the samplerate of the signal we are working with. Affects mel spacing.\n",
    "    :param lowfreq: lowest band edge of mel filters, default 0 Hz\n",
    "    :param highfreq: highest band edge of mel filters, default samplerate/2\n",
    "    :returns: A numpy array of size nfilt * (nfft/2 + 1) containing filterbank. Each row holds 1 filter.\n",
    "    \"\"\"\n",
    "    highfreq = highfreq or samplerate / 2\n",
    "    assert highfreq <= samplerate / 2, \"highfreq is greater than samplerate/2\"\n",
    "\n",
    "    # compute points evenly spaced in mels\n",
    "    lowmel = hz2mel(lowfreq)\n",
    "    highmel = hz2mel(highfreq)\n",
    "    melpoints = np.linspace(lowmel, highmel, nfilt + 2)\n",
    "    # our points are in Hz, but we use fft bins, so we have to convert\n",
    "    #  from Hz to fft bin number\n",
    "    bin = np.floor((nfft + 1) * mel2hz(melpoints) / samplerate)\n",
    "\n",
    "    fbank = np.zeros([nfilt, nfft // 2])\n",
    "    for j in range(0, nfilt):\n",
    "        for i in range(int(bin[j]), int(bin[j + 1])):\n",
    "            fbank[j, i] = (i - bin[j]) / (bin[j + 1] - bin[j])\n",
    "        for i in range(int(bin[j + 1]), int(bin[j + 2])):\n",
    "            fbank[j, i] = (bin[j + 2] - i) / (bin[j + 2] - bin[j + 1])\n",
    "    return fbank\n",
    "\n",
    "\n",
    "def create_mel_filter(\n",
    "    fft_size, n_freq_components=64, start_freq=300, end_freq=8000, samplerate=44100\n",
    "):\n",
    "    \"\"\"\n",
    "    Creates a filter to convolve with the spectrogram to get out mels\n",
    "\n",
    "    \"\"\"\n",
    "    mel_inversion_filter = get_filterbanks(\n",
    "        nfilt=n_freq_components,\n",
    "        nfft=fft_size,\n",
    "        samplerate=samplerate,\n",
    "        lowfreq=start_freq,\n",
    "        highfreq=end_freq,\n",
    "    )\n",
    "    # Normalize filter\n",
    "    mel_filter = mel_inversion_filter.T / mel_inversion_filter.sum(axis=1)\n",
    "\n",
    "    return mel_filter, mel_inversion_filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run params\n",
    "section = 'music'\n",
    "run_id = '0001'\n",
    "data_name = 'musicdata'\n",
    "RUN_FOLDER = 'musicVAE/{}/'.format(section)\n",
    "RUN_FOLDER += '_'.join([run_id, data_name])\n",
    "\n",
    "if not os.path.exists(RUN_FOLDER):\n",
    "    os.mkdir(RUN_FOLDER)\n",
    "    os.mkdir(os.path.join(RUN_FOLDER, 'viz'))\n",
    "    os.mkdir(os.path.join(RUN_FOLDER, 'images'))\n",
    "    os.mkdir(os.path.join(RUN_FOLDER, 'weights'))\n",
    "\n",
    "mode =  'build' #'load' #"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "vae = load_model(VariationalAutoencoder, RUN_FOLDER)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "30"
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vae.z_dim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-1.02339877  0.76620047  0.81855983 -1.16323263  1.86018114  0.26437682\n",
      "  -0.17935176 -0.34196052  0.26054586 -0.14865159 -0.14173734  1.8134282\n",
      "  -0.0574865  -1.9298416   1.97235497  0.51461732 -1.37242056  0.92114772\n",
      "  -1.39336125 -0.40945173 -0.69456544  2.00690525 -0.68920524 -1.31594832\n",
      "   0.46333665 -0.05893291 -0.56736075 -0.31803203  0.89809792 -0.42387937]]\n",
      "(1, 30)\n"
     ]
    }
   ],
   "source": [
    "n_to_show = 1\n",
    "znew = np.random.normal(size = (n_to_show,vae.z_dim))\n",
    "znew.shape\n",
    "print(znew.astype(\"float64\"))\n",
    "print(znew.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(336, 1024)\n",
      "[[2.50764005e-03 1.08882276e-04 9.93849317e-05 ... 2.23336479e-04\n",
      "  3.04785528e-04 3.08300747e-04]\n",
      " [5.41333982e-04 4.02706036e-07 3.08212947e-07 ... 1.60571938e-06\n",
      "  2.59704279e-06 4.06115305e-06]\n",
      " [4.83174081e-04 4.13279423e-07 9.90681201e-07 ... 8.57836312e-06\n",
      "  1.61001954e-05 1.44893347e-05]\n",
      " ...\n",
      " [2.31360827e-04 3.82202046e-07 4.83504436e-06 ... 2.66188090e-05\n",
      "  5.28561213e-05 3.97010845e-05]\n",
      " [2.07971709e-04 4.88308444e-07 3.01968544e-06 ... 3.00065949e-05\n",
      "  3.89641282e-05 5.53828795e-05]\n",
      " [3.41407955e-04 7.79322306e-07 4.62980825e-06 ... 2.49033365e-05\n",
      "  3.26299341e-05 4.37712151e-05]]\n"
     ]
    }
   ],
   "source": [
    "reconst = vae.decoder.predict(np.array(znew))\n",
    "reconst = reconst.reshape(336,1024)\n",
    "reconst = reconst.astype(\"float64\")\n",
    "print(reconst.shape)\n",
    "print(reconst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "fft_size = 2048  # window size for the FFT\n",
    "step_size = fft_size // 16  # distance to slide along the window (in time)\n",
    "spec_thresh = 4  # threshold for spectrograms (lower filters out more noise)\n",
    "lowcut = 500  # Hz # Low cut for our butter bandpass filter\n",
    "highcut = 15000  # Hz # High cut for our butter bandpass filter\n",
    "# For mels\n",
    "n_mel_freq_components = 64  # number of mel frequency channels\n",
    "shorten_factor = 10  # how much should we compress the x-axis (time)\n",
    "start_freq = 300  # Hz # What frequency to start sampling our melS from\n",
    "end_freq = 8000  # Hz # What frequency to stop sampling our melS from"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [],
   "source": [
    "recovered_audio_orig = invert_pretty_spectrogram(\n",
    "    reconst, fft_size=fft_size, step_size=step_size, log=True, n_iter=10\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "rate = 44100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Play the audio\n",
    "IPython.display.Audio(data= recovered_audio_orig, rate=rate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from tqdm import tqdm\n",
    "# import glob\n",
    "# import shutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# source_dir = './musicVAE/data/'\n",
    "# dest_dir = './data/music'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for filename in glob.glob(os.path.join(source_dir, '*.wav')):\n",
    "#     shutil.copy(filename, dest_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for filename in glob.glob(os.path.join(source_dir, '*.txt')):\n",
    "#     shutil.copy(filename, dest_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for filename in tqdm(glob.glob(os.path.join(source_dir, '*.wav'))):\n",
    "#     os.remove(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for filename in tqdm(glob.glob(os.path.join(source_dir, '*.txt'))):\n",
    "#     os.remove(filename)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}