01-speech-commands-mfcc-extraction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from os import listdir\n",
    "from os.path import isdir, join\n",
    "import librosa\n",
    "import random\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import python_speech_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: playsound in /usr/local/lib/python3.8/dist-packages (1.3.0)\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "! python3 -m pip install playsound"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nine\n",
      "eight\n",
      "bed\n",
      "bird\n",
      "no\n",
      "house\n",
      "go\n",
      "zero\n",
      "marvin\n",
      "dog\n",
      "off\n",
      "_background_noise_\n",
      "happy\n",
      "stop\n",
      "left\n",
      "two\n",
      "yes\n",
      "on\n",
      "learn\n",
      "three\n",
      "wow\n",
      "tree\n",
      "cat\n",
      "right\n",
      "down\n",
      "six\n",
      "five\n",
      "backward\n",
      "sheila\n",
      "one\n",
      "up\n",
      "follow\n",
      "visual\n",
      "forward\n",
      "seven\n",
      "four\n"
     ]
    }
   ],
   "source": [
    "# set dataset path\n",
    "dataset_path = './data_speech_commands_v002'\n",
    "\n",
    "import os\n",
    "# get speech_commands from google's server\n",
    "if not os.path.exists(dataset_path):\n",
    "    if not os.path.isfile('speech_commands_v0.02.tar.gz') :\n",
    "        !wget https://storage.googleapis.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz\n",
    "    !mkdir data_speech_commands_v002\n",
    "    !tar zxvf \"./speech_commands_v0.02.tar.gz\" --directory data_speech_commands_v002\n",
    "    \n",
    "# Dataset path and view possible targets\n",
    "dataset_path = dataset_path\n",
    "for name in listdir(dataset_path):\n",
    "    if isdir(join(dataset_path, name)):\n",
    "        print(name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['nine', 'eight', 'bed', 'bird', 'no', 'house', 'go', 'zero', 'marvin', 'dog', 'off', '_background_noise_', 'happy', 'stop', 'left', 'two', 'yes', 'on', 'learn', 'three', 'wow', 'tree', 'cat', 'right', 'down', 'six', 'five', 'backward', 'sheila', 'one', 'up', 'follow', 'visual', 'forward', 'seven', 'four']\n"
     ]
    }
   ],
   "source": [
    "# Create an all targets list\n",
    "all_targets = [name for name in listdir(dataset_path) if isdir(join(dataset_path, name))]\n",
    "print(all_targets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['nine', 'eight', 'bed', 'bird', 'no', 'house', 'go', 'zero', 'marvin', 'dog', 'off', 'happy', 'stop', 'left', 'two', 'yes', 'on', 'learn', 'three', 'wow', 'tree', 'cat', 'right', 'down', 'six', 'five', 'backward', 'sheila', 'one', 'up', 'follow', 'visual', 'forward', 'seven', 'four']\n"
     ]
    }
   ],
   "source": [
    "# Leave off background noise set\n",
    "all_targets.remove('_background_noise_')\n",
    "print(all_targets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3934\n",
      "3787\n",
      "2014\n",
      "2064\n",
      "3941\n",
      "2113\n",
      "3880\n",
      "4052\n",
      "2100\n",
      "2128\n",
      "3745\n",
      "2054\n",
      "3872\n",
      "3801\n",
      "3880\n",
      "4044\n",
      "3845\n",
      "1575\n",
      "3727\n",
      "2123\n",
      "1759\n",
      "2031\n",
      "3778\n",
      "3917\n",
      "3860\n",
      "4052\n",
      "1664\n",
      "2022\n",
      "3890\n",
      "3723\n",
      "1579\n",
      "1592\n",
      "1557\n",
      "3998\n",
      "3728\n",
      "Total samples: 105829\n"
     ]
    }
   ],
   "source": [
    "# See how many files are in each\n",
    "num_samples = 0\n",
    "for target in all_targets:\n",
    "    print(len(listdir(join(dataset_path, target))))\n",
    "    num_samples += len(listdir(join(dataset_path, target)))\n",
    "print('Total samples:', num_samples)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Settings\n",
    "target_list = all_targets\n",
    "feature_sets_file = 'all_targets_mfcc_sets.npz'\n",
    "perc_keep_samples = 1.0 # 1.0 is keep all samples\n",
    "val_ratio = 0.1\n",
    "test_ratio = 0.1\n",
    "sample_rate = 8000\n",
    "num_mfcc = 16\n",
    "len_mfcc = 16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./data_speech_commands_v002/nine\n",
      "./data_speech_commands_v002/eight\n",
      "./data_speech_commands_v002/bed\n",
      "./data_speech_commands_v002/bird\n",
      "./data_speech_commands_v002/no\n",
      "./data_speech_commands_v002/house\n",
      "./data_speech_commands_v002/go\n",
      "./data_speech_commands_v002/zero\n",
      "./data_speech_commands_v002/marvin\n",
      "./data_speech_commands_v002/dog\n",
      "./data_speech_commands_v002/off\n",
      "./data_speech_commands_v002/happy\n",
      "./data_speech_commands_v002/stop\n",
      "./data_speech_commands_v002/left\n",
      "./data_speech_commands_v002/two\n",
      "./data_speech_commands_v002/yes\n",
      "./data_speech_commands_v002/on\n",
      "./data_speech_commands_v002/learn\n",
      "./data_speech_commands_v002/three\n",
      "./data_speech_commands_v002/wow\n",
      "./data_speech_commands_v002/tree\n",
      "./data_speech_commands_v002/cat\n",
      "./data_speech_commands_v002/right\n",
      "./data_speech_commands_v002/down\n",
      "./data_speech_commands_v002/six\n",
      "./data_speech_commands_v002/five\n",
      "./data_speech_commands_v002/backward\n",
      "./data_speech_commands_v002/sheila\n",
      "./data_speech_commands_v002/one\n",
      "./data_speech_commands_v002/up\n",
      "./data_speech_commands_v002/follow\n",
      "./data_speech_commands_v002/visual\n",
      "./data_speech_commands_v002/forward\n",
      "./data_speech_commands_v002/seven\n",
      "./data_speech_commands_v002/four\n"
     ]
    }
   ],
   "source": [
    "# Create list of filenames along with ground truth vector (y)\n",
    "filenames = []\n",
    "y = []\n",
    "for index, target in enumerate(target_list):\n",
    "    print(join(dataset_path, target))\n",
    "    filenames.append(listdir(join(dataset_path, target)))\n",
    "    y.append(np.ones(len(filenames[index])) * index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[array([0., 0., 0., ..., 0., 0., 0.]), array([1., 1., 1., ..., 1., 1., 1.]), array([2., 2., 2., ..., 2., 2., 2.]), array([3., 3., 3., ..., 3., 3., 3.]), array([4., 4., 4., ..., 4., 4., 4.]), array([5., 5., 5., ..., 5., 5., 5.]), array([6., 6., 6., ..., 6., 6., 6.]), array([7., 7., 7., ..., 7., 7., 7.]), array([8., 8., 8., ..., 8., 8., 8.]), array([9., 9., 9., ..., 9., 9., 9.]), array([10., 10., 10., ..., 10., 10., 10.]), array([11., 11., 11., ..., 11., 11., 11.]), array([12., 12., 12., ..., 12., 12., 12.]), array([13., 13., 13., ..., 13., 13., 13.]), array([14., 14., 14., ..., 14., 14., 14.]), array([15., 15., 15., ..., 15., 15., 15.]), array([16., 16., 16., ..., 16., 16., 16.]), array([17., 17., 17., ..., 17., 17., 17.]), array([18., 18., 18., ..., 18., 18., 18.]), array([19., 19., 19., ..., 19., 19., 19.]), array([20., 20., 20., ..., 20., 20., 20.]), array([21., 21., 21., ..., 21., 21., 21.]), array([22., 22., 22., ..., 22., 22., 22.]), array([23., 23., 23., ..., 23., 23., 23.]), array([24., 24., 24., ..., 24., 24., 24.]), array([25., 25., 25., ..., 25., 25., 25.]), array([26., 26., 26., ..., 26., 26., 26.]), array([27., 27., 27., ..., 27., 27., 27.]), array([28., 28., 28., ..., 28., 28., 28.]), array([29., 29., 29., ..., 29., 29., 29.]), array([30., 30., 30., ..., 30., 30., 30.]), array([31., 31., 31., ..., 31., 31., 31.]), array([32., 32., 32., ..., 32., 32., 32.]), array([33., 33., 33., ..., 33., 33., 33.]), array([34., 34., 34., ..., 34., 34., 34.])]\n",
      "3934\n",
      "3787\n",
      "2014\n",
      "2064\n",
      "3941\n",
      "2113\n",
      "3880\n",
      "4052\n",
      "2100\n",
      "2128\n",
      "3745\n",
      "2054\n",
      "3872\n",
      "3801\n",
      "3880\n",
      "4044\n",
      "3845\n",
      "1575\n",
      "3727\n",
      "2123\n",
      "1759\n",
      "2031\n",
      "3778\n",
      "3917\n",
      "3860\n",
      "4052\n",
      "1664\n",
      "2022\n",
      "3890\n",
      "3723\n",
      "1579\n",
      "1592\n",
      "1557\n",
      "3998\n",
      "3728\n"
     ]
    }
   ],
   "source": [
    "# Check ground truth Y vector\n",
    "print(y)\n",
    "for item in y:\n",
    "    print(len(item))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Flatten filename and y vectors\n",
    "filenames = [item for sublist in filenames for item in sublist]\n",
    "y = [item for sublist in y for item in sublist]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Associate filenames with true output and shuffle\n",
    "filenames_y = list(zip(filenames, y))\n",
    "random.shuffle(filenames_y)\n",
    "filenames, y = zip(*filenames_y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "105829\n",
      "105829\n"
     ]
    }
   ],
   "source": [
    "# Only keep the specified number of samples (shorter extraction/training)\n",
    "print(len(filenames))\n",
    "filenames = filenames[:int(len(filenames) * perc_keep_samples)]\n",
    "print(len(filenames))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate validation and test set sizes\n",
    "val_set_size = int(len(filenames) * val_ratio)\n",
    "test_set_size = int(len(filenames) * test_ratio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Break dataset apart into train, validation, and test sets\n",
    "filenames_val = filenames[:val_set_size]\n",
    "filenames_test = filenames[val_set_size:(val_set_size + test_set_size)]\n",
    "filenames_train = filenames[(val_set_size + test_set_size):]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Break y apart into train, validation, and test sets\n",
    "y_orig_val = y[:val_set_size]\n",
    "y_orig_test = y[val_set_size:(val_set_size + test_set_size)]\n",
    "y_orig_train = y[(val_set_size + test_set_size):]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function: Create MFCC from given path\n",
    "def calc_mfcc(path):\n",
    "    \n",
    "    # Load wavefile\n",
    "    signal, fs = librosa.load(path, sr=sample_rate)\n",
    "    \n",
    "    # Create MFCCs from sound clip\n",
    "    mfccs = python_speech_features.base.mfcc(signal, \n",
    "                                            samplerate=fs,\n",
    "                                            winlen=0.256,\n",
    "                                            winstep=0.050,\n",
    "                                            numcep=num_mfcc,\n",
    "                                            nfilt=26,\n",
    "                                            nfft=2048,\n",
    "                                            preemph=0.0,\n",
    "                                            ceplifter=0,\n",
    "                                            appendEnergy=False,\n",
    "                                            winfunc=np.hanning)\n",
    "    return mfccs.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped: 18 (16, 12)\n",
      "Dropped: 41 (16, 7)\n",
      "Dropped: 43 (16, 13)\n",
      "Dropped: 51 (16, 13)\n",
      "Dropped: 100 (16, 10)\n",
      "Dropped: 103 (16, 13)\n",
      "Dropped: 109 (16, 15)\n",
      "Dropped: 112 (16, 13)\n",
      "Dropped: 116 (16, 15)\n",
      "Dropped: 129 (16, 11)\n",
      "Dropped: 130 (16, 12)\n",
      "Dropped: 133 (16, 12)\n",
      "Dropped: 169 (16, 15)\n",
      "Dropped: 170 (16, 13)\n",
      "Dropped: 191 (16, 11)\n",
      "Dropped: 198 (16, 9)\n",
      "Dropped: 229 (16, 13)\n",
      "Dropped: 234 (16, 15)\n",
      "Dropped: 240 (16, 14)\n",
      "Dropped: 256 (16, 7)\n",
      "Dropped: 257 (16, 15)\n",
      "Dropped: 271 (16, 13)\n",
      "Dropped: 276 (16, 9)\n",
      "Dropped: 303 (16, 15)\n",
      "Dropped: 305 (16, 15)\n",
      "Dropped: 357 (16, 11)\n",
      "Dropped: 363 (16, 12)\n",
      "Dropped: 403 (16, 13)\n",
      "Dropped: 426 (16, 14)\n",
      "Dropped: 428 (16, 11)\n",
      "Dropped: 438 (16, 14)\n",
      "Dropped: 454 (16, 6)\n",
      "Dropped: 466 (16, 9)\n",
      "Dropped: 474 (16, 12)\n",
      "Dropped: 490 (16, 15)\n"
     ]
    }
   ],
   "source": [
    "# TEST: Construct test set by computing MFCC of each WAV file\n",
    "prob_cnt = 0\n",
    "x_test = []\n",
    "y_test = []\n",
    "for index, filename in enumerate(filenames_train):\n",
    "    \n",
    "    # Stop after 500\n",
    "    if index >= 500:\n",
    "        break\n",
    "    \n",
    "    # Create path from given filename and target item\n",
    "    path = join(dataset_path, target_list[int(y_orig_train[index])], \n",
    "                filename)\n",
    "    \n",
    "    # Create MFCCs\n",
    "    mfccs = calc_mfcc(path)\n",
    "    \n",
    "    if mfccs.shape[1] == len_mfcc:\n",
    "        x_test.append(mfccs)\n",
    "        y_test.append(y_orig_train[index])\n",
    "    else:\n",
    "        print('Dropped:', index, mfccs.shape)\n",
    "        prob_cnt += 1\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "% of problematic samples: 0.07\n"
     ]
    }
   ],
   "source": [
    "print('% of problematic samples:', prob_cnt / 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "playsound is relying on another python subprocess. Please use `pip install pygobject` if you want playsound to run more efficiently.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MFCCs: [[-4.68040519e+01 -4.20935592e+01 -4.00342461e+01 -4.04233688e+01\n",
      "  -4.28051255e+01 -4.20863068e+01 -3.83852202e+01 -3.58303140e+01\n",
      "  -3.36559319e+01 -3.40492767e+01 -3.89869293e+01 -5.11707034e+01\n",
      "  -6.37560692e+01 -7.11872000e+01 -7.76703854e+01 -8.20364479e+01]\n",
      " [ 2.27562743e+01  2.50567506e+01  2.60887569e+01  2.65285445e+01\n",
      "   2.64659059e+01  2.44122095e+01  2.04447268e+01  1.66254761e+01\n",
      "   1.15221889e+01  7.29767772e+00  4.20654180e+00  1.78365876e+00\n",
      "   3.16840672e+00  4.12514170e+00  4.48721179e+00  4.59693295e+00]\n",
      " [ 5.18965491e+00  5.14602423e+00  4.94444482e+00  5.44538596e+00\n",
      "   6.68890312e+00  5.37464407e+00  3.67006703e+00  3.80771881e+00\n",
      "   4.90066083e+00  4.74459602e+00  3.47172811e+00  1.25189223e+00\n",
      "  -3.49141193e-01  2.91652468e-01  1.55751076e+00  2.86406272e+00]\n",
      " [-6.83883114e+00 -8.49413266e+00 -8.57080822e+00 -7.46742945e+00\n",
      "  -5.85817800e+00 -4.18672142e+00 -2.82613784e+00 -1.45725311e+00\n",
      "   3.81155782e-01  7.37675750e-01  2.59160606e-01 -8.28352439e-01\n",
      "   9.00472732e-01  2.54392574e+00  3.54884268e+00  2.97510434e+00]\n",
      " [-3.63408958e+00 -3.10177604e+00 -2.83296946e+00 -2.74280725e+00\n",
      "  -2.84918837e+00 -7.82482436e-01  1.19447603e+00  1.44050193e+00\n",
      "   1.84503658e-01  7.65509943e-02 -4.74180051e-02 -2.31709226e-01\n",
      "   1.96284785e+00  1.98185442e+00  1.37595277e+00  2.91382704e-01]\n",
      " [-9.19921445e-01 -7.76449499e-01 -6.65771522e-01  4.62841539e-02\n",
      "   5.47629938e-01  4.19155243e-02 -1.52197420e+00 -2.56150711e+00\n",
      "  -3.11590611e+00 -2.23964683e+00 -1.68908190e+00 -1.48329943e+00\n",
      "  -2.69678191e-01 -9.51301971e-01 -1.15942974e+00 -2.58255495e-02]\n",
      " [-3.22393087e+00 -3.02834260e+00 -3.07951065e+00 -3.03331347e+00\n",
      "  -2.60658282e+00 -4.07684911e+00 -4.28537256e+00 -3.53907199e+00\n",
      "  -1.20418454e+00  7.94117116e-03  3.25959207e-01 -9.35979206e-02\n",
      "  -1.31156023e+00 -1.77147702e+00 -1.60993431e+00 -9.50338260e-01]\n",
      " [-2.06882960e+00 -2.60283514e+00 -2.69858570e+00 -2.38535619e+00\n",
      "  -2.02116625e+00 -9.49322092e-01  5.64301415e-01  2.47908538e+00\n",
      "   2.70043903e+00  2.00383861e+00  1.89441361e+00  1.98367949e+00\n",
      "   6.16270320e-01 -4.80395161e-01 -1.07720579e+00 -1.45155434e+00]\n",
      " [-2.63197423e+00 -1.99320297e+00 -1.75007907e+00 -1.84545004e+00\n",
      "  -2.19773358e+00 -1.05304293e-01  1.66710055e+00  1.47648224e+00\n",
      "   6.14381434e-01 -3.35486017e-02 -2.19073433e-01 -5.35890503e-01\n",
      "  -2.80108723e+00 -2.22970056e+00 -1.23963093e+00 -1.51745462e+00]\n",
      " [ 1.77963932e+00  1.53798173e+00  1.14026486e+00  1.37333653e+00\n",
      "   1.36054502e+00 -1.98926389e-01 -1.60455863e+00 -1.94132279e+00\n",
      "  -8.38747958e-01  2.35697110e-01  6.51150173e-01  1.00892342e+00\n",
      "  -1.40857271e-02 -8.86166364e-01 -9.97679064e-01 -8.35624220e-01]\n",
      " [-1.54336657e+00 -1.37886005e+00 -6.30458653e-01  1.64833020e-01\n",
      "   2.94028828e-01 -1.16782623e+00 -1.27409421e+00 -1.33590347e+00\n",
      "  -1.86508616e+00 -1.18206392e+00 -4.55699261e-01  6.54177792e-01\n",
      "   6.28435607e-02 -1.64854554e-01 -6.73627103e-01 -8.02664932e-01]\n",
      " [-9.94192627e-01 -1.46376200e+00 -1.71158930e+00 -1.41451064e+00\n",
      "  -8.15823982e-01 -2.16863243e-01 -5.09824967e-01 -1.17753674e+00\n",
      "  -9.13270154e-01 -1.27683553e+00 -1.32569137e+00 -1.43188723e+00\n",
      "  -2.27056479e+00 -1.88051107e+00 -8.26165955e-01 -3.94318621e-01]\n",
      " [-2.27594601e+00 -2.68192498e+00 -2.59755168e+00 -2.12794585e+00\n",
      "  -1.89682382e+00 -7.78663470e-01 -1.43938091e+00 -1.23409594e+00\n",
      "  -1.09985071e+00 -1.22362179e+00 -9.88717352e-01 -8.78857479e-01\n",
      "  -1.71270019e+00 -2.06847832e+00 -1.63579848e+00 -1.17747574e+00]\n",
      " [-1.59239892e+00 -9.76616099e-01 -6.86600332e-01 -8.36220871e-01\n",
      "  -9.82668882e-01 -7.08461696e-01 -2.91620553e-01 -1.06334880e-01\n",
      "  -8.70418964e-01 -6.46348661e-01 -3.94698975e-01 -2.43631878e-01\n",
      "  -8.18032395e-02 -5.21330002e-02 -4.05125450e-01  4.37719881e-02]\n",
      " [-8.52963357e-02 -5.69325507e-01 -1.10207657e+00 -1.35080850e+00\n",
      "  -1.46836219e+00 -2.06299707e+00 -8.08724169e-01 -4.38781039e-02\n",
      "   5.65521814e-01  5.12487023e-01  1.50701346e-01 -2.90127961e-01\n",
      "  -2.76639851e-01 -3.27290946e-02 -6.06931229e-01 -4.68606910e-01]\n",
      " [ 4.50179538e-01  8.17551285e-01  1.13411423e+00  9.38028343e-01\n",
      "   4.87559733e-01  8.08402835e-01  9.84347731e-01  1.07473005e+00\n",
      "   8.75206588e-01  3.18021765e-03 -4.15147543e-01  2.12827763e-01\n",
      "   3.92503455e-01  1.82534732e-01  4.55843342e-01  5.45243597e-01]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f07e5f47a60>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TEST: Test shorter MFCC\n",
    "# !pip install playsound\n",
    "from playsound import playsound\n",
    "\n",
    "idx = 13\n",
    "\n",
    "# Create path from given filename and target item\n",
    "path = join(dataset_path, target_list[int(y_orig_train[idx])], \n",
    "            filenames_train[idx])\n",
    "\n",
    "# Create MFCCs\n",
    "mfccs = calc_mfcc(path)\n",
    "print(\"MFCCs:\", mfccs)\n",
    "\n",
    "# Plot MFCC\n",
    "fig = plt.figure()\n",
    "plt.imshow(mfccs, cmap='inferno', origin='lower')\n",
    "\n",
    "# TEST: Play problem sounds\n",
    "#print(target_list[int(y_orig_train[idx])])\n",
    "#playsound(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function: Create MFCCs, keeping only ones of desired length\n",
    "def extract_features(in_files, in_y):\n",
    "    prob_cnt = 0\n",
    "    out_x = []\n",
    "    out_y = []\n",
    "        \n",
    "    for index, filename in enumerate(in_files):\n",
    "    \n",
    "        # Create path from given filename and target item\n",
    "        path = join(dataset_path, target_list[int(in_y[index])], \n",
    "                    filename)\n",
    "        \n",
    "        # Check to make sure we're reading a .wav file\n",
    "        if not path.endswith('.wav'):\n",
    "            continue\n",
    "\n",
    "        # Create MFCCs\n",
    "        mfccs = calc_mfcc(path)\n",
    "\n",
    "        # Only keep MFCCs with given length\n",
    "        if mfccs.shape[1] == len_mfcc:\n",
    "            out_x.append(mfccs)\n",
    "            out_y.append(in_y[index])\n",
    "        else:\n",
    "            print('Dropped:', index, mfccs.shape)\n",
    "            prob_cnt += 1\n",
    "            \n",
    "    return out_x, out_y, prob_cnt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Dropped: 20799 (16, 15)\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped: 24930 (16, 14)\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
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     "output_type": "stream",
     "text": [
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     ]
    },
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
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     "output_type": "stream",
     "text": [
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     ]
    },
    {
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     "output_type": "stream",
     "text": [
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      "Dropped: 81857 (16, 8)\n",
      "Dropped: 81865 (16, 12)\n",
      "Dropped: 81867 (16, 9)\n",
      "Dropped: 81902 (16, 11)\n",
      "Dropped: 81907 (16, 8)\n",
      "Dropped: 81911 (16, 15)\n",
      "Dropped: 81913 (16, 14)\n",
      "Dropped: 81935 (16, 14)\n",
      "Dropped: 81946 (16, 11)\n",
      "Dropped: 81961 (16, 10)\n",
      "Dropped: 81974 (16, 9)\n",
      "Dropped: 81976 (16, 11)\n",
      "Dropped: 82012 (16, 12)\n",
      "Dropped: 82047 (16, 12)\n",
      "Dropped: 82061 (16, 13)\n",
      "Dropped: 82081 (16, 8)\n",
      "Dropped: 82096 (16, 13)\n",
      "Dropped: 82105 (16, 9)\n",
      "Dropped: 82118 (16, 14)\n",
      "Dropped: 82126 (16, 11)\n",
      "Dropped: 82152 (16, 4)\n",
      "Dropped: 82193 (16, 13)\n",
      "Dropped: 82214 (16, 14)\n",
      "Dropped: 82252 (16, 5)\n",
      "Dropped: 82256 (16, 12)\n",
      "Dropped: 82259 (16, 11)\n",
      "Dropped: 82263 (16, 15)\n",
      "Dropped: 82270 (16, 13)\n",
      "Dropped: 82281 (16, 13)\n",
      "Dropped: 82284 (16, 12)\n",
      "Dropped: 82287 (16, 13)\n",
      "Dropped: 82290 (16, 14)\n",
      "Dropped: 82292 (16, 9)\n",
      "Dropped: 82297 (16, 14)\n",
      "Dropped: 82298 (16, 14)\n",
      "Dropped: 82307 (16, 12)\n",
      "Dropped: 82335 (16, 12)\n",
      "Dropped: 82337 (16, 11)\n",
      "Dropped: 82363 (16, 14)\n",
      "Dropped: 82376 (16, 10)\n",
      "Dropped: 82383 (16, 14)\n",
      "Dropped: 82406 (16, 15)\n",
      "Dropped: 82407 (16, 13)\n",
      "Dropped: 82418 (16, 12)\n",
      "Dropped: 82423 (16, 14)\n",
      "Dropped: 82424 (16, 13)\n",
      "Dropped: 82461 (16, 13)\n",
      "Dropped: 82472 (16, 13)\n",
      "Dropped: 82487 (16, 14)\n",
      "Dropped: 82534 (16, 14)\n",
      "Dropped: 82547 (16, 13)\n",
      "Dropped: 82553 (16, 13)\n",
      "Dropped: 82555 (16, 13)\n",
      "Dropped: 82562 (16, 15)\n",
      "Dropped: 82565 (16, 13)\n",
      "Dropped: 82572 (16, 13)\n",
      "Dropped: 82602 (16, 11)\n",
      "Dropped: 82609 (16, 12)\n",
      "Dropped: 82614 (16, 10)\n",
      "Dropped: 82626 (16, 9)\n",
      "Dropped: 82638 (16, 9)\n",
      "Dropped: 82640 (16, 10)\n",
      "Dropped: 82653 (16, 14)\n",
      "Dropped: 82658 (16, 10)\n",
      "Dropped: 82672 (16, 13)\n",
      "Dropped: 82675 (16, 13)\n",
      "Dropped: 82691 (16, 11)\n",
      "Dropped: 82700 (16, 7)\n",
      "Dropped: 82728 (16, 11)\n",
      "Dropped: 82731 (16, 10)\n",
      "Dropped: 82737 (16, 14)\n",
      "Dropped: 82748 (16, 11)\n",
      "Dropped: 82757 (16, 11)\n",
      "Dropped: 82773 (16, 8)\n",
      "Dropped: 82784 (16, 12)\n",
      "Dropped: 82794 (16, 6)\n",
      "Dropped: 82801 (16, 13)\n",
      "Dropped: 82810 (16, 13)\n",
      "Dropped: 82817 (16, 14)\n",
      "Dropped: 82869 (16, 14)\n",
      "Dropped: 82887 (16, 6)\n",
      "Dropped: 82892 (16, 15)\n",
      "Dropped: 82910 (16, 13)\n",
      "Dropped: 82915 (16, 13)\n",
      "Dropped: 82942 (16, 12)\n",
      "Dropped: 82964 (16, 13)\n",
      "Dropped: 82975 (16, 15)\n",
      "Dropped: 82978 (16, 14)\n",
      "Dropped: 83012 (16, 14)\n",
      "Dropped: 83052 (16, 14)\n",
      "Dropped: 83059 (16, 13)\n",
      "Dropped: 83060 (16, 7)\n",
      "Dropped: 83066 (16, 12)\n",
      "Dropped: 83069 (16, 3)\n",
      "Dropped: 83075 (16, 13)\n",
      "Dropped: 83076 (16, 13)\n",
      "Dropped: 83098 (16, 12)\n",
      "Dropped: 83127 (16, 13)\n",
      "Dropped: 83132 (16, 10)\n",
      "Dropped: 83147 (16, 12)\n",
      "Dropped: 83154 (16, 14)\n",
      "Dropped: 83155 (16, 14)\n",
      "Dropped: 83168 (16, 9)\n",
      "Dropped: 83179 (16, 11)\n",
      "Dropped: 83182 (16, 10)\n",
      "Dropped: 83190 (16, 12)\n",
      "Dropped: 83203 (16, 12)\n",
      "Dropped: 83207 (16, 12)\n",
      "Dropped: 83208 (16, 5)\n",
      "Dropped: 83215 (16, 14)\n",
      "Dropped: 83255 (16, 13)\n",
      "Dropped: 83261 (16, 13)\n",
      "Dropped: 83263 (16, 14)\n",
      "Dropped: 83266 (16, 11)\n",
      "Dropped: 83327 (16, 11)\n",
      "Dropped: 83337 (16, 15)\n",
      "Dropped: 83341 (16, 11)\n",
      "Dropped: 83363 (16, 14)\n",
      "Dropped: 83367 (16, 15)\n",
      "Dropped: 83378 (16, 15)\n",
      "Dropped: 83379 (16, 8)\n",
      "Dropped: 83389 (16, 13)\n",
      "Dropped: 83399 (16, 12)\n",
      "Dropped: 83404 (16, 14)\n",
      "Dropped: 83460 (16, 11)\n",
      "Dropped: 83470 (16, 12)\n",
      "Dropped: 83480 (16, 13)\n",
      "Dropped: 83496 (16, 13)\n",
      "Dropped: 83499 (16, 13)\n",
      "Dropped: 83533 (16, 10)\n",
      "Dropped: 83553 (16, 13)\n",
      "Dropped: 83578 (16, 12)\n",
      "Dropped: 83590 (16, 15)\n",
      "Dropped: 83595 (16, 13)\n",
      "Dropped: 83626 (16, 8)\n",
      "Dropped: 83640 (16, 14)\n",
      "Dropped: 83657 (16, 6)\n",
      "Dropped: 83665 (16, 14)\n",
      "Dropped: 83704 (16, 10)\n",
      "Dropped: 83710 (16, 3)\n",
      "Dropped: 83747 (16, 13)\n",
      "Dropped: 83784 (16, 7)\n",
      "Dropped: 83800 (16, 14)\n",
      "Dropped: 83810 (16, 12)\n",
      "Dropped: 83817 (16, 7)\n",
      "Dropped: 83838 (16, 13)\n",
      "Dropped: 83842 (16, 10)\n",
      "Dropped: 83847 (16, 7)\n",
      "Dropped: 83849 (16, 15)\n",
      "Dropped: 83863 (16, 13)\n",
      "Dropped: 83881 (16, 12)\n",
      "Dropped: 83886 (16, 8)\n",
      "Dropped: 83897 (16, 15)\n",
      "Dropped: 83900 (16, 6)\n",
      "Dropped: 83925 (16, 11)\n",
      "Dropped: 83946 (16, 12)\n",
      "Dropped: 83966 (16, 12)\n",
      "Dropped: 83967 (16, 8)\n",
      "Dropped: 83972 (16, 13)\n",
      "Dropped: 83980 (16, 11)\n",
      "Dropped: 83982 (16, 10)\n",
      "Dropped: 83989 (16, 7)\n",
      "Dropped: 84008 (16, 14)\n",
      "Dropped: 84020 (16, 11)\n",
      "Dropped: 84025 (16, 12)\n",
      "Dropped: 84035 (16, 11)\n",
      "Dropped: 84038 (16, 12)\n",
      "Dropped: 84040 (16, 13)\n",
      "Dropped: 84067 (16, 15)\n",
      "Dropped: 84085 (16, 13)\n",
      "Dropped: 84108 (16, 12)\n",
      "Dropped: 84116 (16, 4)\n",
      "Dropped: 84155 (16, 11)\n",
      "Dropped: 84173 (16, 13)\n",
      "Dropped: 84182 (16, 11)\n",
      "Dropped: 84191 (16, 15)\n",
      "Dropped: 84208 (16, 12)\n",
      "Dropped: 84230 (16, 14)\n",
      "Dropped: 84249 (16, 15)\n",
      "Dropped: 84268 (16, 13)\n",
      "Dropped: 84273 (16, 11)\n",
      "Dropped: 84292 (16, 9)\n",
      "Dropped: 84303 (16, 14)\n",
      "Dropped: 84323 (16, 7)\n",
      "Dropped: 84331 (16, 12)\n",
      "Dropped: 84347 (16, 7)\n",
      "Dropped: 84351 (16, 15)\n",
      "Dropped: 84352 (16, 7)\n",
      "Dropped: 84361 (16, 11)\n",
      "Dropped: 84364 (16, 15)\n",
      "Dropped: 84366 (16, 7)\n",
      "Dropped: 84385 (16, 13)\n",
      "Dropped: 84394 (16, 8)\n",
      "Dropped: 84403 (16, 12)\n",
      "Dropped: 84418 (16, 11)\n",
      "Dropped: 84430 (16, 12)\n",
      "Dropped: 84446 (16, 12)\n",
      "Dropped: 84451 (16, 6)\n",
      "Dropped: 84477 (16, 15)\n",
      "Dropped: 84480 (16, 12)\n",
      "Dropped: 84485 (16, 11)\n",
      "Dropped: 84505 (16, 13)\n",
      "Dropped: 84513 (16, 11)\n",
      "Dropped: 84515 (16, 13)\n",
      "Dropped: 84560 (16, 11)\n",
      "Dropped: 84572 (16, 14)\n",
      "Dropped: 84586 (16, 13)\n",
      "Dropped: 84587 (16, 12)\n",
      "Dropped: 84589 (16, 13)\n",
      "Dropped: 84596 (16, 15)\n",
      "Dropped: 84615 (16, 10)\n",
      "Dropped: 84625 (16, 11)\n",
      "Dropped: 84629 (16, 14)\n",
      "Dropped: 84639 (16, 15)\n",
      "Dropped: 84643 (16, 13)\n",
      "Dropped: 84646 (16, 11)\n",
      "Dropped: 84653 (16, 11)\n",
      "Removed percentage: 0.08466308391897479\n",
      "Dropped: 6 (16, 13)\n",
      "Dropped: 43 (16, 13)\n",
      "Dropped: 49 (16, 13)\n",
      "Dropped: 69 (16, 8)\n",
      "Dropped: 75 (16, 14)\n",
      "Dropped: 91 (16, 9)\n",
      "Dropped: 93 (16, 13)\n",
      "Dropped: 113 (16, 14)\n",
      "Dropped: 115 (16, 15)\n",
      "Dropped: 151 (16, 12)\n",
      "Dropped: 154 (16, 15)\n",
      "Dropped: 155 (16, 7)\n",
      "Dropped: 165 (16, 11)\n",
      "Dropped: 173 (16, 9)\n",
      "Dropped: 186 (16, 15)\n",
      "Dropped: 194 (16, 12)\n",
      "Dropped: 201 (16, 13)\n",
      "Dropped: 205 (16, 3)\n",
      "Dropped: 211 (16, 15)\n",
      "Dropped: 219 (16, 15)\n",
      "Dropped: 223 (16, 12)\n",
      "Dropped: 234 (16, 12)\n",
      "Dropped: 239 (16, 12)\n",
      "Dropped: 246 (16, 14)\n",
      "Dropped: 283 (16, 11)\n",
      "Dropped: 285 (16, 15)\n",
      "Dropped: 300 (16, 13)\n",
      "Dropped: 336 (16, 13)\n",
      "Dropped: 338 (16, 13)\n",
      "Dropped: 341 (16, 10)\n",
      "Dropped: 400 (16, 15)\n",
      "Dropped: 404 (16, 15)\n",
      "Dropped: 405 (16, 7)\n",
      "Dropped: 406 (16, 10)\n",
      "Dropped: 407 (16, 13)\n",
      "Dropped: 426 (16, 13)\n",
      "Dropped: 443 (16, 12)\n",
      "Dropped: 454 (16, 14)\n",
      "Dropped: 463 (16, 14)\n",
      "Dropped: 466 (16, 13)\n",
      "Dropped: 485 (16, 13)\n",
      "Dropped: 488 (16, 12)\n",
      "Dropped: 494 (16, 14)\n",
      "Dropped: 513 (16, 8)\n",
      "Dropped: 530 (16, 15)\n",
      "Dropped: 538 (16, 15)\n",
      "Dropped: 579 (16, 14)\n",
      "Dropped: 590 (16, 12)\n",
      "Dropped: 592 (16, 11)\n",
      "Dropped: 593 (16, 12)\n",
      "Dropped: 595 (16, 11)\n",
      "Dropped: 597 (16, 4)\n",
      "Dropped: 610 (16, 10)\n",
      "Dropped: 619 (16, 14)\n",
      "Dropped: 625 (16, 7)\n",
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      "Dropped: 675 (16, 13)\n",
      "Dropped: 683 (16, 11)\n",
      "Dropped: 698 (16, 15)\n",
      "Dropped: 704 (16, 13)\n",
      "Dropped: 716 (16, 14)\n",
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      "Dropped: 871 (16, 13)\n",
      "Dropped: 878 (16, 10)\n",
      "Dropped: 882 (16, 11)\n",
      "Dropped: 892 (16, 14)\n",
      "Dropped: 894 (16, 13)\n",
      "Dropped: 900 (16, 10)\n",
      "Dropped: 901 (16, 13)\n",
      "Dropped: 903 (16, 13)\n",
      "Dropped: 915 (16, 15)\n",
      "Dropped: 916 (16, 14)\n",
      "Dropped: 955 (16, 7)\n",
      "Dropped: 982 (16, 12)\n",
      "Dropped: 987 (16, 13)\n",
      "Dropped: 1009 (16, 12)\n",
      "Dropped: 1038 (16, 8)\n",
      "Dropped: 1048 (16, 9)\n",
      "Dropped: 1052 (16, 14)\n",
      "Dropped: 1062 (16, 14)\n",
      "Dropped: 1072 (16, 11)\n",
      "Dropped: 1083 (16, 7)\n",
      "Dropped: 1094 (16, 15)\n",
      "Dropped: 1096 (16, 13)\n",
      "Dropped: 1107 (16, 2)\n",
      "Dropped: 1134 (16, 12)\n",
      "Dropped: 1153 (16, 7)\n",
      "Dropped: 1155 (16, 11)\n",
      "Dropped: 1162 (16, 14)\n",
      "Dropped: 1165 (16, 11)\n",
      "Dropped: 1183 (16, 9)\n",
      "Dropped: 1184 (16, 15)\n",
      "Dropped: 1198 (16, 15)\n",
      "Dropped: 1202 (16, 11)\n",
      "Dropped: 1218 (16, 11)\n",
      "Dropped: 1226 (16, 13)\n",
      "Dropped: 1241 (16, 15)\n",
      "Dropped: 1244 (16, 13)\n",
      "Dropped: 1248 (16, 9)\n",
      "Dropped: 1259 (16, 11)\n",
      "Dropped: 1279 (16, 8)\n",
      "Dropped: 1287 (16, 8)\n",
      "Dropped: 1319 (16, 13)\n",
      "Dropped: 1330 (16, 10)\n",
      "Dropped: 1341 (16, 12)\n",
      "Dropped: 1427 (16, 14)\n",
      "Dropped: 1448 (16, 15)\n",
      "Dropped: 1477 (16, 11)\n",
      "Dropped: 1481 (16, 15)\n",
      "Dropped: 1484 (16, 11)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped: 1495 (16, 15)\n",
      "Dropped: 1507 (16, 13)\n",
      "Dropped: 1511 (16, 15)\n",
      "Dropped: 1517 (16, 10)\n",
      "Dropped: 1533 (16, 15)\n",
      "Dropped: 1539 (16, 9)\n",
      "Dropped: 1540 (16, 13)\n",
      "Dropped: 1562 (16, 13)\n",
      "Dropped: 1603 (16, 3)\n",
      "Dropped: 1605 (16, 15)\n",
      "Dropped: 1654 (16, 13)\n",
      "Dropped: 1667 (16, 10)\n",
      "Dropped: 1685 (16, 12)\n",
      "Dropped: 1701 (16, 11)\n",
      "Dropped: 1703 (16, 15)\n",
      "Dropped: 1730 (16, 15)\n",
      "Dropped: 1733 (16, 12)\n",
      "Dropped: 1739 (16, 13)\n",
      "Dropped: 1748 (16, 13)\n",
      "Dropped: 1762 (16, 12)\n",
      "Dropped: 1765 (16, 15)\n",
      "Dropped: 1786 (16, 15)\n",
      "Dropped: 1804 (16, 15)\n",
      "Dropped: 1808 (16, 13)\n",
      "Dropped: 1827 (16, 13)\n",
      "Dropped: 1860 (16, 6)\n",
      "Dropped: 1875 (16, 13)\n",
      "Dropped: 1898 (16, 9)\n",
      "Dropped: 1901 (16, 14)\n",
      "Dropped: 1903 (16, 13)\n",
      "Dropped: 1912 (16, 10)\n",
      "Dropped: 1957 (16, 8)\n",
      "Dropped: 1967 (16, 10)\n",
      "Dropped: 1969 (16, 14)\n",
      "Dropped: 1986 (16, 5)\n",
      "Dropped: 1989 (16, 14)\n",
      "Dropped: 1992 (16, 14)\n",
      "Dropped: 2011 (16, 14)\n",
      "Dropped: 2019 (16, 13)\n",
      "Dropped: 2039 (16, 12)\n",
      "Dropped: 2048 (16, 15)\n",
      "Dropped: 2077 (16, 13)\n",
      "Dropped: 2086 (16, 13)\n",
      "Dropped: 2092 (16, 15)\n",
      "Dropped: 2097 (16, 13)\n",
      "Dropped: 2105 (16, 8)\n",
      "Dropped: 2111 (16, 13)\n",
      "Dropped: 2137 (16, 13)\n",
      "Dropped: 2151 (16, 15)\n",
      "Dropped: 2171 (16, 8)\n",
      "Dropped: 2195 (16, 12)\n",
      "Dropped: 2199 (16, 13)\n",
      "Dropped: 2206 (16, 13)\n",
      "Dropped: 2239 (16, 13)\n",
      "Dropped: 2272 (16, 8)\n",
      "Dropped: 2286 (16, 11)\n",
      "Dropped: 2303 (16, 8)\n",
      "Dropped: 2308 (16, 9)\n",
      "Dropped: 2322 (16, 11)\n",
      "Dropped: 2326 (16, 15)\n",
      "Dropped: 2330 (16, 11)\n",
      "Dropped: 2331 (16, 15)\n",
      "Dropped: 2336 (16, 10)\n",
      "Dropped: 2337 (16, 14)\n",
      "Dropped: 2367 (16, 13)\n",
      "Dropped: 2375 (16, 11)\n",
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      "Dropped: 2400 (16, 15)\n",
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      "Dropped: 2457 (16, 9)\n",
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      "Dropped: 2500 (16, 13)\n",
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      "Dropped: 2788 (16, 14)\n",
      "Dropped: 2789 (16, 7)\n",
      "Dropped: 2797 (16, 8)\n",
      "Dropped: 2847 (16, 9)\n",
      "Dropped: 2852 (16, 14)\n",
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      "Dropped: 2894 (16, 9)\n",
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      "Dropped: 2960 (16, 2)\n",
      "Dropped: 2999 (16, 7)\n",
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      "Dropped: 3103 (16, 14)\n",
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      "Dropped: 3170 (16, 8)\n",
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      "Dropped: 3215 (16, 15)\n",
      "Dropped: 3219 (16, 11)\n",
      "Dropped: 3234 (16, 14)\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Dropped: 8714 (16, 12)\n",
      "Dropped: 8716 (16, 15)\n",
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      "Dropped: 8772 (16, 12)\n",
      "Dropped: 8775 (16, 8)\n",
      "Dropped: 8780 (16, 13)\n",
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      "Dropped: 8794 (16, 15)\n",
      "Dropped: 8820 (16, 11)\n",
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      "Dropped: 8853 (16, 13)\n",
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      "Dropped: 8863 (16, 13)\n",
      "Dropped: 8881 (16, 14)\n",
      "Dropped: 8898 (16, 14)\n",
      "Dropped: 8927 (16, 9)\n",
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      "Dropped: 9101 (16, 10)\n",
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      "Dropped: 9109 (16, 13)\n",
      "Dropped: 9121 (16, 3)\n",
      "Dropped: 9138 (16, 12)\n",
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      "Dropped: 9257 (16, 7)\n",
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      "Dropped: 9300 (16, 13)\n",
      "Dropped: 9316 (16, 11)\n",
      "Dropped: 9328 (16, 12)\n",
      "Dropped: 9336 (16, 11)\n",
      "Dropped: 9353 (16, 14)\n",
      "Dropped: 9374 (16, 4)\n",
      "Dropped: 9383 (16, 11)\n",
      "Dropped: 9391 (16, 14)\n",
      "Dropped: 9426 (16, 13)\n",
      "Dropped: 9436 (16, 7)\n",
      "Dropped: 9438 (16, 13)\n",
      "Dropped: 9452 (16, 14)\n",
      "Dropped: 9453 (16, 14)\n",
      "Dropped: 9459 (16, 11)\n",
      "Dropped: 9463 (16, 14)\n",
      "Dropped: 9464 (16, 9)\n",
      "Dropped: 9468 (16, 12)\n",
      "Dropped: 9477 (16, 12)\n",
      "Dropped: 9496 (16, 13)\n",
      "Dropped: 9521 (16, 12)\n",
      "Dropped: 9526 (16, 11)\n",
      "Dropped: 9531 (16, 11)\n",
      "Dropped: 9555 (16, 15)\n",
      "Dropped: 9562 (16, 5)\n",
      "Dropped: 9578 (16, 14)\n",
      "Dropped: 9585 (16, 14)\n",
      "Dropped: 9589 (16, 10)\n",
      "Dropped: 9595 (16, 13)\n",
      "Dropped: 9608 (16, 14)\n",
      "Dropped: 9618 (16, 5)\n",
      "Dropped: 9626 (16, 11)\n",
      "Dropped: 9627 (16, 15)\n",
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      "Dropped: 9632 (16, 15)\n",
      "Dropped: 9642 (16, 13)\n",
      "Dropped: 9654 (16, 12)\n",
      "Dropped: 9662 (16, 15)\n",
      "Dropped: 9665 (16, 15)\n",
      "Dropped: 9668 (16, 15)\n",
      "Dropped: 9687 (16, 15)\n",
      "Dropped: 9713 (16, 8)\n",
      "Dropped: 9732 (16, 13)\n",
      "Dropped: 9756 (16, 13)\n",
      "Dropped: 9779 (16, 12)\n",
      "Dropped: 9789 (16, 14)\n",
      "Dropped: 9794 (16, 12)\n",
      "Dropped: 9800 (16, 11)\n",
      "Dropped: 9801 (16, 12)\n",
      "Dropped: 9821 (16, 13)\n",
      "Dropped: 9823 (16, 15)\n",
      "Dropped: 9831 (16, 15)\n",
      "Dropped: 9837 (16, 11)\n",
      "Dropped: 9846 (16, 11)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped: 9861 (16, 10)\n",
      "Dropped: 9886 (16, 9)\n",
      "Dropped: 9895 (16, 11)\n",
      "Dropped: 9898 (16, 13)\n",
      "Dropped: 9906 (16, 14)\n",
      "Dropped: 9920 (16, 14)\n",
      "Dropped: 9927 (16, 9)\n",
      "Dropped: 9964 (16, 14)\n",
      "Dropped: 9967 (16, 11)\n",
      "Dropped: 9972 (16, 11)\n",
      "Dropped: 9978 (16, 14)\n",
      "Dropped: 9981 (16, 11)\n",
      "Dropped: 9985 (16, 11)\n",
      "Dropped: 10002 (16, 15)\n",
      "Dropped: 10017 (16, 12)\n",
      "Dropped: 10024 (16, 15)\n",
      "Dropped: 10027 (16, 11)\n",
      "Dropped: 10030 (16, 13)\n",
      "Dropped: 10051 (16, 13)\n",
      "Dropped: 10081 (16, 15)\n",
      "Dropped: 10110 (16, 8)\n",
      "Dropped: 10113 (16, 14)\n",
      "Dropped: 10125 (16, 8)\n",
      "Dropped: 10132 (16, 11)\n",
      "Dropped: 10142 (16, 12)\n",
      "Dropped: 10149 (16, 10)\n",
      "Dropped: 10158 (16, 12)\n",
      "Dropped: 10173 (16, 13)\n",
      "Dropped: 10177 (16, 12)\n",
      "Dropped: 10186 (16, 11)\n",
      "Dropped: 10190 (16, 12)\n",
      "Dropped: 10195 (16, 14)\n",
      "Dropped: 10196 (16, 8)\n",
      "Dropped: 10203 (16, 13)\n",
      "Dropped: 10217 (16, 13)\n",
      "Dropped: 10224 (16, 15)\n",
      "Dropped: 10227 (16, 12)\n",
      "Dropped: 10229 (16, 11)\n",
      "Dropped: 10232 (16, 7)\n",
      "Dropped: 10233 (16, 8)\n",
      "Dropped: 10242 (16, 10)\n",
      "Dropped: 10247 (16, 11)\n",
      "Dropped: 10268 (16, 14)\n",
      "Dropped: 10290 (16, 14)\n",
      "Dropped: 10293 (16, 12)\n",
      "Dropped: 10297 (16, 15)\n",
      "Dropped: 10317 (16, 13)\n",
      "Dropped: 10340 (16, 9)\n",
      "Dropped: 10343 (16, 9)\n",
      "Dropped: 10374 (16, 7)\n",
      "Dropped: 10382 (16, 11)\n",
      "Dropped: 10404 (16, 13)\n",
      "Dropped: 10408 (16, 10)\n",
      "Dropped: 10418 (16, 11)\n",
      "Dropped: 10426 (16, 11)\n",
      "Dropped: 10458 (16, 12)\n",
      "Dropped: 10461 (16, 13)\n",
      "Dropped: 10494 (16, 14)\n",
      "Dropped: 10496 (16, 15)\n",
      "Dropped: 10499 (16, 15)\n",
      "Dropped: 10501 (16, 12)\n",
      "Dropped: 10502 (16, 15)\n",
      "Dropped: 10513 (16, 10)\n",
      "Dropped: 10518 (16, 11)\n",
      "Dropped: 10532 (16, 14)\n",
      "Dropped: 10542 (16, 15)\n",
      "Dropped: 10551 (16, 13)\n",
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      "Dropped: 10566 (16, 13)\n",
      "Dropped: 10572 (16, 15)\n",
      "Dropped: 10574 (16, 11)\n",
      "Removed percentage: 0.08618408618408618\n",
      "Dropped: 17 (16, 9)\n",
      "Dropped: 35 (16, 15)\n",
      "Dropped: 38 (16, 14)\n",
      "Dropped: 46 (16, 14)\n",
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      "Dropped: 55 (16, 14)\n",
      "Dropped: 57 (16, 13)\n",
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      "Dropped: 66 (16, 12)\n",
      "Dropped: 70 (16, 6)\n",
      "Dropped: 84 (16, 8)\n",
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      "Dropped: 87 (16, 14)\n",
      "Dropped: 96 (16, 15)\n",
      "Dropped: 97 (16, 13)\n",
      "Dropped: 116 (16, 10)\n",
      "Dropped: 132 (16, 15)\n",
      "Dropped: 150 (16, 15)\n",
      "Dropped: 179 (16, 11)\n",
      "Dropped: 181 (16, 14)\n",
      "Dropped: 186 (16, 13)\n",
      "Dropped: 200 (16, 14)\n",
      "Dropped: 208 (16, 13)\n",
      "Dropped: 217 (16, 12)\n",
      "Dropped: 238 (16, 12)\n",
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      "Dropped: 261 (16, 14)\n",
      "Dropped: 264 (16, 14)\n",
      "Dropped: 267 (16, 10)\n",
      "Dropped: 275 (16, 8)\n",
      "Dropped: 351 (16, 13)\n",
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      "Dropped: 364 (16, 11)\n",
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      "Dropped: 400 (16, 14)\n",
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      "Dropped: 412 (16, 6)\n",
      "Dropped: 436 (16, 15)\n",
      "Dropped: 454 (16, 8)\n",
      "Dropped: 462 (16, 12)\n",
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      "Dropped: 474 (16, 13)\n",
      "Dropped: 481 (16, 11)\n",
      "Dropped: 510 (16, 14)\n",
      "Dropped: 558 (16, 9)\n",
      "Dropped: 567 (16, 9)\n",
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      "Dropped: 1001 (16, 12)\n",
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      "Dropped: 1896 (16, 15)\n",
      "Dropped: 1912 (16, 13)\n",
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      "Dropped: 1917 (16, 13)\n",
      "Dropped: 1925 (16, 10)\n",
      "Dropped: 1935 (16, 12)\n",
      "Dropped: 1959 (16, 13)\n",
      "Dropped: 1970 (16, 11)\n",
      "Dropped: 1972 (16, 15)\n",
      "Dropped: 2027 (16, 11)\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dropped: 3482 (16, 14)\n",
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      "Dropped: 3505 (16, 10)\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "Dropped: 10203 (16, 10)\n",
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      "Dropped: 10219 (16, 11)\n",
      "Dropped: 10253 (16, 7)\n",
      "Dropped: 10271 (16, 13)\n",
      "Dropped: 10276 (16, 15)\n",
      "Dropped: 10280 (16, 15)\n",
      "Dropped: 10287 (16, 9)\n",
      "Dropped: 10294 (16, 11)\n",
      "Dropped: 10297 (16, 15)\n",
      "Dropped: 10303 (16, 8)\n",
      "Dropped: 10332 (16, 12)\n",
      "Dropped: 10348 (16, 12)\n",
      "Dropped: 10349 (16, 14)\n",
      "Dropped: 10350 (16, 15)\n",
      "Dropped: 10361 (16, 12)\n",
      "Dropped: 10366 (16, 11)\n",
      "Dropped: 10394 (16, 15)\n",
      "Dropped: 10414 (16, 13)\n",
      "Dropped: 10417 (16, 13)\n",
      "Dropped: 10449 (16, 11)\n",
      "Dropped: 10453 (16, 14)\n",
      "Dropped: 10467 (16, 15)\n",
      "Dropped: 10472 (16, 5)\n",
      "Dropped: 10491 (16, 7)\n",
      "Dropped: 10495 (16, 11)\n",
      "Dropped: 10524 (16, 5)\n",
      "Dropped: 10539 (16, 12)\n",
      "Dropped: 10558 (16, 8)\n",
      "Dropped: 10565 (16, 14)\n",
      "Dropped: 10566 (16, 11)\n",
      "Removed percentage: 0.08438858438858439\n"
     ]
    }
   ],
   "source": [
    "# Create train, validation, and test sets\n",
    "x_train, y_train, prob = extract_features(filenames_train, \n",
    "                                          y_orig_train)\n",
    "print('Removed percentage:', prob / len(y_orig_train))\n",
    "x_val, y_val, prob = extract_features(filenames_val, y_orig_val)\n",
    "print('Removed percentage:', prob / len(y_orig_val))\n",
    "x_test, y_test, prob = extract_features(filenames_test, y_orig_test)\n",
    "print('Removed percentage:', prob / len(y_orig_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save features and truth vector (y) sets to disk\n",
    "np.savez(feature_sets_file, \n",
    "         x_train=x_train, \n",
    "         y_train=y_train, \n",
    "         x_val=x_val, \n",
    "         y_val=y_val, \n",
    "         x_test=x_test, \n",
    "         y_test=y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['x_train', 'y_train', 'x_val', 'y_val', 'x_test', 'y_test']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TEST: Load features\n",
    "feature_sets = np.load(feature_sets_file)\n",
    "feature_sets.files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77497"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(feature_sets['x_train'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[12. 34. 30. ... 19. 18. 32.]\n"
     ]
    }
   ],
   "source": [
    "print(feature_sets['y_val'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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