create_csv.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import glob\n",
    "import numpy as np\n",
    "import python_speech_features as mfcc\n",
    "from scipy.io.wavfile import read\n",
    "import random\n",
    "import regex as re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "LABELS = {\n",
    "    \"en\": 0,\n",
    "    \"ur\": 1,\n",
    "    \"ue\": 2\n",
    "}\n",
    "NUM_CLASSES = 3\n",
    "NUM_FEATURES = 13\n",
    "\n",
    "RANDOM_SEED = 50\n",
    "\n",
    "TRAIN_DATASET_GLOB = \"sampled_dataset/train/*\"\n",
    "TEST_DATASET_GLOB = \"sampled_dataset/test/*\"\n",
    "\n",
    "SHUMAIL_DATASET = \"shumail2/*\"\n",
    "\n",
    "DATASPLIT = 0.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_MFCC(audio, sr):\n",
    "    features = mfcc.mfcc(audio, sr, 0.025, 0.01, 13, appendEnergy=True)\n",
    "    return np.mean(features, axis=0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:frame length (800) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (800) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (800) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "<ipython-input-22-71033bca7ebf>:11: WavFileWarning: Chunk (non-data) not understood, skipping it.\n",
      "  sr, audio = read(path)\n",
      "WARNING:root:frame length (800) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1600) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1600) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1600) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1600) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
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      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (4800) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n",
      "WARNING:root:frame length (1103) is greater than FFT size (512), frame will be truncated. Increase NFFT to avoid.\n"
     ]
    }
   ],
   "source": [
    "data = []\n",
    "labels = []\n",
    "\n",
    "for path in glob.glob(\"Recordings/*\"):\n",
    "    label = path.split(\"\\\\\")[1]\n",
    "    label = re.split(r\"-|_\", label)[0]\n",
    "    y = np.zeros((NUM_CLASSES))\n",
    "    try: \n",
    "        labels.append(LABELS[label])\n",
    "\n",
    "        sr, audio = read(path)\n",
    "        features = get_MFCC(audio, sr)\n",
    "        \n",
    "        data.append(features)\n",
    "    except KeyError: \n",
    "        print(KeyError, path)\n",
    "        break\n",
    "\n",
    "sample_index = list(range(0, len(data)))\n",
    "random.shuffle(sample_index)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17380"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
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       "      <th>3</th>\n",
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       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>LABEL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>14.443077</td>\n",
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       "      <th>1</th>\n",
       "      <td>10.219182</td>\n",
       "      <td>1.742702</td>\n",
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       "      <th>2</th>\n",
       "      <td>13.876193</td>\n",
       "      <td>1.004525</td>\n",
       "      <td>-10.143044</td>\n",
       "      <td>4.769317</td>\n",
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       "      <th>3</th>\n",
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       "      <td>-6.122454</td>\n",
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       "      <td>-10.869105</td>\n",
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       "      <td>-5.230862</td>\n",
       "      <td>-0.560520</td>\n",
       "      <td>-4.260071</td>\n",
       "      <td>-8.647045</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16.165702</td>\n",
       "      <td>7.492517</td>\n",
       "      <td>-18.944081</td>\n",
       "      <td>-11.769776</td>\n",
       "      <td>0.360446</td>\n",
       "      <td>-10.676715</td>\n",
       "      <td>-10.353008</td>\n",
       "      <td>7.848967</td>\n",
       "      <td>0.781196</td>\n",
       "      <td>-0.323822</td>\n",
       "      <td>-6.596552</td>\n",
       "      <td>-6.907072</td>\n",
       "      <td>-4.249575</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
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       "      <th>17375</th>\n",
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       "      <td>0.449793</td>\n",
       "      <td>8.464243</td>\n",
       "      <td>13.715499</td>\n",
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       "      <td>2.922420</td>\n",
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       "      <td>4.728756</td>\n",
       "      <td>-3.520493</td>\n",
       "      <td>6.343505</td>\n",
       "      <td>1.306161</td>\n",
       "      <td>-3.577430</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>17376</th>\n",
       "      <td>10.832928</td>\n",
       "      <td>5.712939</td>\n",
       "      <td>6.460498</td>\n",
       "      <td>0.479978</td>\n",
       "      <td>-9.827152</td>\n",
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       "      <td>-16.057971</td>\n",
       "      <td>-7.821987</td>\n",
       "      <td>-7.278880</td>\n",
       "      <td>-8.225414</td>\n",
       "      <td>-1.474205</td>\n",
       "      <td>-10.781243</td>\n",
       "      <td>-8.982661</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>17377</th>\n",
       "      <td>15.653813</td>\n",
       "      <td>-6.198936</td>\n",
       "      <td>-0.756519</td>\n",
       "      <td>-0.182128</td>\n",
       "      <td>-5.058881</td>\n",
       "      <td>-12.113604</td>\n",
       "      <td>-15.959658</td>\n",
       "      <td>-1.984598</td>\n",
       "      <td>-3.341601</td>\n",
       "      <td>-5.365412</td>\n",
       "      <td>0.485510</td>\n",
       "      <td>-4.278507</td>\n",
       "      <td>-10.961661</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>17378</th>\n",
       "      <td>14.656198</td>\n",
       "      <td>2.442599</td>\n",
       "      <td>-1.116128</td>\n",
       "      <td>-3.430590</td>\n",
       "      <td>-9.892589</td>\n",
       "      <td>-16.597521</td>\n",
       "      <td>-17.447496</td>\n",
       "      <td>-1.346676</td>\n",
       "      <td>-11.960978</td>\n",
       "      <td>-9.395277</td>\n",
       "      <td>-5.763173</td>\n",
       "      <td>-7.353033</td>\n",
       "      <td>-8.212849</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17379</th>\n",
       "      <td>10.457680</td>\n",
       "      <td>0.415493</td>\n",
       "      <td>-3.733206</td>\n",
       "      <td>5.588005</td>\n",
       "      <td>3.902790</td>\n",
       "      <td>-2.029628</td>\n",
       "      <td>-11.010215</td>\n",
       "      <td>-17.936656</td>\n",
       "      <td>-7.469568</td>\n",
       "      <td>-7.055387</td>\n",
       "      <td>-4.272895</td>\n",
       "      <td>-6.074557</td>\n",
       "      <td>-4.459090</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17380 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               0         1          2          3          4          5  \\\n",
       "0      14.443077 -8.036094  -4.077253  -0.274023  -9.003208 -17.048237   \n",
       "1      10.219182  1.742702   1.002258  -2.806073 -14.951893 -21.500796   \n",
       "2      13.876193  1.004525 -10.143044   4.769317 -25.268881 -12.703184   \n",
       "3      12.510054 -3.575093  -4.913943  -6.122454  -3.552648  -9.513949   \n",
       "4      16.165702  7.492517 -18.944081 -11.769776   0.360446 -10.676715   \n",
       "...          ...       ...        ...        ...        ...        ...   \n",
       "17375  12.577980  0.449793   8.464243  13.715499  -1.113134   2.922420   \n",
       "17376  10.832928  5.712939   6.460498   0.479978  -9.827152  -8.491606   \n",
       "17377  15.653813 -6.198936  -0.756519  -0.182128  -5.058881 -12.113604   \n",
       "17378  14.656198  2.442599  -1.116128  -3.430590  -9.892589 -16.597521   \n",
       "17379  10.457680  0.415493  -3.733206   5.588005   3.902790  -2.029628   \n",
       "\n",
       "               6          7          8          9        10         11  \\\n",
       "0     -21.399697 -16.263466   3.396780 -12.284809  0.908476 -10.026655   \n",
       "1     -13.495337  -9.305933  -7.441661  -1.825364 -8.279968   0.422083   \n",
       "2     -17.730170  -6.543746 -15.888943  -2.577060 -9.861565   1.551331   \n",
       "3     -10.869105  -8.880711   1.368740  -5.230862 -0.560520  -4.260071   \n",
       "4     -10.353008   7.848967   0.781196  -0.323822 -6.596552  -6.907072   \n",
       "...          ...        ...        ...        ...       ...        ...   \n",
       "17375  -6.761397   2.240919   4.728756  -3.520493  6.343505   1.306161   \n",
       "17376 -16.057971  -7.821987  -7.278880  -8.225414 -1.474205 -10.781243   \n",
       "17377 -15.959658  -1.984598  -3.341601  -5.365412  0.485510  -4.278507   \n",
       "17378 -17.447496  -1.346676 -11.960978  -9.395277 -5.763173  -7.353033   \n",
       "17379 -11.010215 -17.936656  -7.469568  -7.055387 -4.272895  -6.074557   \n",
       "\n",
       "              12  LABEL  \n",
       "0      -4.254287      0  \n",
       "1      -3.959009      0  \n",
       "2      -3.312003      0  \n",
       "3      -8.647045      0  \n",
       "4      -4.249575      0  \n",
       "...          ...    ...  \n",
       "17375  -3.577430      1  \n",
       "17376  -8.982661      1  \n",
       "17377 -10.961661      1  \n",
       "17378  -8.212849      1  \n",
       "17379  -4.459090      1  \n",
       "\n",
       "[17380 rows x 14 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(data=data)\n",
    "df[\"LABEL\"] = labels\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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