Audio cleaning 6 labels.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os \n",
    "from tqdm import tqdm\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.io import wavfile\n",
    "from python_speech_features import mfcc, logfbank\n",
    "import librosa\n",
    "import wave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_signals(signals):\n",
    "    fig, axes = plt.subplots(nrows=2, ncols=6, sharex=False,\n",
    "                             sharey=True, figsize=(20,5))\n",
    "    fig.suptitle('Time Series', size=16)\n",
    "    i = 0\n",
    "    for x in range(1):\n",
    "        for y in range(6):\n",
    "            axes[x,y].set_title(list(signals.keys())[i])\n",
    "            axes[x,y].plot(list(signals.values())[i])\n",
    "            axes[x,y].get_xaxis().set_visible(False)\n",
    "            axes[x,y].get_yaxis().set_visible(False)\n",
    "            i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_fft(fft):\n",
    "    fig, axes = plt.subplots(nrows=2, ncols=6, sharex=False,\n",
    "                             sharey=True, figsize=(20,5))\n",
    "    fig.suptitle('Fourier Transforms', size=16)\n",
    "    i = 0\n",
    "    for x in range(1):\n",
    "        for y in range(6):\n",
    "            data = list(fft.values())[i]\n",
    "            Y, freq = data[0], data[1]\n",
    "            axes[x,y].set_title(list(fft.keys())[i])\n",
    "            axes[x,y].plot(freq, Y)\n",
    "            axes[x,y].get_xaxis().set_visible(False)\n",
    "            axes[x,y].get_yaxis().set_visible(False)\n",
    "            i += 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_fbank(fbank):\n",
    "    fig, axes = plt.subplots(nrows=2, ncols=6, sharex=False,\n",
    "                             sharey=True, figsize=(20,5))\n",
    "    fig.suptitle('Filter Bank Coefficients', size=16)\n",
    "    i = 0\n",
    "    for x in range(1):\n",
    "        for y in range(6):\n",
    "            axes[x,y].set_title(list(fbank.keys())[i])\n",
    "            axes[x,y].imshow(list(fbank.values())[i],\n",
    "                    cmap='hot', interpolation='nearest')\n",
    "            axes[x,y].get_xaxis().set_visible(False)\n",
    "            axes[x,y].get_yaxis().set_visible(False)\n",
    "            i += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_mfccs(mfccs):\n",
    "    fig, axes = plt.subplots(nrows=2, ncols=6, sharex=False,\n",
    "                             sharey=True, figsize=(20,5))\n",
    "    fig.suptitle('Mel Frequency Cepstrum Coefficients', size=16)\n",
    "    i = 0\n",
    "    for x in range(1):\n",
    "        for y in range(6):\n",
    "            axes[x,y].set_title(list(mfccs.keys())[i])\n",
    "            axes[x,y].imshow(list(mfccs.values())[i],\n",
    "                    cmap='hot', interpolation='nearest')\n",
    "            axes[x,y].get_xaxis().set_visible(False)\n",
    "            axes[x,y].get_yaxis().set_visible(False)\n",
    "            i += 1\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('./audio2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>audiofile</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>conv35.wav</td>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>conv17.wav</td>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>conv10.wav</td>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>conv11.wav</td>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>conv44.wav</td>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    audiofile          label\n",
       "0  conv35.wav  Conversations\n",
       "1  conv17.wav  Conversations\n",
       "2  conv10.wav  Conversations\n",
       "3  conv11.wav  Conversations\n",
       "4  conv44.wav  Conversations"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('audiofile',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>audiofile</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>conv35.wav</th>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv17.wav</th>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv10.wav</th>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv11.wav</th>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv44.wav</th>\n",
       "      <td>Conversations</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    label\n",
       "audiofile                \n",
       "conv35.wav  Conversations\n",
       "conv17.wav  Conversations\n",
       "conv10.wav  Conversations\n",
       "conv11.wav  Conversations\n",
       "conv44.wav  Conversations"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# count=0\n",
    "# for f in df.index:\n",
    "#     print(f)\n",
    "    \n",
    "#     rate, signal = wavfile.read('wavfiles/'+f)\n",
    "#     print(rate,signal)\n",
    "#     count+=1\n",
    "#     print(f)\n",
    "# print(count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "for f in df.index:\n",
    "#     print(f)\n",
    "    rate, signal = wavfile.read('data/'+f)\n",
    "#     print(signal.shape)\n",
    "    df.at[f,'length']=signal.shape[0]/rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>label</th>\n",
       "      <th>length</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>audiofile</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>conv35.wav</th>\n",
       "      <td>Conversations</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv17.wav</th>\n",
       "      <td>Conversations</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv10.wav</th>\n",
       "      <td>Conversations</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv11.wav</th>\n",
       "      <td>Conversations</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>conv44.wav</th>\n",
       "      <td>Conversations</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    label  length\n",
       "audiofile                        \n",
       "conv35.wav  Conversations     2.0\n",
       "conv17.wav  Conversations     2.0\n",
       "conv10.wav  Conversations     2.0\n",
       "conv11.wav  Conversations     2.0\n",
       "conv44.wav  Conversations     2.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "classes = list(np.unique(df.label))\n",
    "class_dist = df.groupby(['label'])['length'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax= plt.subplots()\n",
    "ax.set_title('class_distribution',y=1.08)\n",
    "ax.pie(class_dist,labels=class_dist.index, autopct='%1.1f%%',shadow= False, startangle=90)\n",
    "ax.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "signals={}\n",
    "fft={}\n",
    "filter_banks={}\n",
    "mfcc_dict= {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculating fft\n",
    "def cal_fft(y,rate):\n",
    "    n=len(y)\n",
    "    frequency=np.fft.rfftfreq(n,d=1/rate)\n",
    "    Y=abs(np.fft.rfft(y)/n)\n",
    "    return (Y,frequency)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#envolope function for removing the dead signals and for rolling window in the signal\n",
    "\n",
    "def envolope(y,rate, threshold):\n",
    "    mask=[]\n",
    "    y=pd.Series(y).apply(np.abs)\n",
    "    y_mean=y.rolling(window=int(rate/10),min_periods=1,center=True).mean()\n",
    "    \n",
    "    for mean in y_mean:\n",
    "        \n",
    "        if mean > threshold :\n",
    "            mask.append(True)\n",
    "        else:\n",
    "            mask.append(False)\n",
    "            \n",
    "    return mask\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in classes:\n",
    "    wave_file=df[df.label==c].iloc[0,0]\n",
    "    signal,rate=librosa.load('data/'+wave_file,sr=44100)\n",
    "#     print(signal,rate)\n",
    "    mask=envolope(signal,rate,0.0005)\n",
    "    signal=signal[mask]\n",
    "    signals[c]=signal\n",
    "    fft[c]=cal_fft(signal,rate)\n",
    "    \n",
    "    bank=logfbank(signal[:rate],rate, nfilt=26, nfft=1103).T\n",
    "    filter_banks[c]=bank\n",
    "#     44100/40=1102.5\n",
    "    mel=mfcc(signal[:rate],rate,numcep=13,nfilt=26,nfft=1103).T\n",
    "    mfcc_dict[c]=mel\n",
    "    \n",
    "\n",
    "# print(fft)\n",
    "# plot_fft(fft)\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ry/mrM/MyYAnw7HLe+ZQH8IgYCxxRToMiKXRCZs7MzJUUPzpvj/VbSJxUtpxaXpazHbBXmUW+IzMXAWTmpZn5j7LFyA3AVRQ7aSP+Dbg0M6/OzNXAd4DNKE4cO52emY9n5nyKH7yDar77TsAe5ff/c2aaVGpt46jbX8q7YE9FxPKIeHlmXp+Z92RmR3mn7nyKBGlPpmfmzzNzLXAWRVztEEVrvCOAT5X7whzg+xQX9Z0ez8wflncilm+4aQC+mZlPZeajwHU8HcPvBH5Q7ocLgG9W+3OojXS2Vnot8ADw2ACW9efMvLLcz35Dkbj/ZnmMvgCYEBFbN7B/vBP478ycUR6/v9FdgZk5pfwdWFn+1n2P3vdbtZ8NfgNqzKLmbnEFbwf+mJk3ludDJ1JcYHfq6TzsPcAvM/Nv5bpfAF4S64+b8Y3MnF9zLjUW2BeIzHwgM2f1oc4SAOW5+Espbqr+HJhbtpjbgSLBf1rZWiLL4+z0mtVPL4/PyylufI3PzFMyc1VmTi23d1RZzh2ZeUt5rjON4uZC/TH6tMxclJn3AfcCV2Xm1MxcSNFz4XkD9ofQsNVLDL8H+F4ZR0sojrFH1V2vnlyeg9wD/C/rJy/vyKJnw2qK84pNKZKeZOZvyuvLjsy8EHiY4qZBp+6uDXan2F9OLM9ZbqS4Pu20HcXvUW9+lZn3lfvUSuBCiiQsEfEcita3f2xgOy3BpNLGmweMi+67u+xMceer0/Ry2rr1606ullFkcaHIor41imbabwX+VvNjsgdwSXkx/hTFRcpaitYWnWozrGdT3K2+oGxieFpnprfMKt8SRdPvpyguMho9sVvv+2VmR1nuLjXLPNHN9/s2MAW4Kopud8c3WKaGrw32l8z858zcupw3Ioqun9eVzbcXUiRQe4vHdTGWmcvKt1tQ7CebALNq9pX/AbavWbe3OxHrbZ/1Y3jnuvUb2Zba09kUrU0/wMDfuZpd8345xUX82prP0Nj+UR/ftb9l64mIHSLigii60C2iaInVlwSBWtuTdH/OtFM5v6r14rRsZT2vbn5352H15zBLynVrz2Fqt30txV32M4A5EfGzKLr0SX1WJic/kJm7UrQI2plirNbdKFpjdKf2+LwHxXAVT9Ucz79IeV0QRTfoP0YxtMYiinFg64/R9b8d9Z+3QOpCDzHc1fF3FN1fr9ZfJ9cefzsoerjsDBAR74uIu2ri/QDWj+nurg12BhaUvxW15XaaR/F71Jv6c/6zgHeXraGOBi4qk01twaTSxvsrxUBk3XV7eZziQN9p93JarzLzfoogP5z1u75BEciHZ+bWNa9NM7P27nfWbGt1Zp6cmftTtCJ6A/C+MmH1fxQtjHYoL+4vo+jKsN42Gvl+5Y60Gw3chc9iPJ3PZOYzKZr0fjoiNhgATS2lc3/paRD784CJwG6ZuRXwUxqPx3ozyvLG1ewnW2bmc2qW2ZjWcbNYv5vFbhuxLbWw8obAIxRJ+9/WzV7K+gN379jTpvqxWr3tH7NYP6Z372FbXy/rdmBmbklxt67HpzmqLXX+Bry1dmJEbEFxrvMnet8f6veB9eI0IjanuNPcqafzsPpzmGeU63Z5LgWQmadn5gsousPtQzHguNQvMvNBim7JB1Aco5/V0+I172cAj9RdF4zNzCPK+T8BHgT2Lo/RX8RjtAZAXQx3dfxdw/oJy/rzjMe7mhfFuLu7Ao9HxB4UraKOA7Yrr1/vpbGYngVsUx7va8vtdA1wSETsSs/qfxtuAVZR9PZ5N8XNxLZhUmkjlU1Cv0wxFtKbI2LziNikbP1zGkXXnS9FxPgoHin9ZaqNpXEe8B8Uffh/UzP9p8Cp5U5Fuf1uL9Qj4lURcWA5nsciiibcHRRP2xoDzAXWlIOY1T5OfTawXWw4qFqni4DXR8ShZcunz1CcMP6lty8WEW+IiL3KRNRCipZWHb2spmEsM5+i6Hrw44h4e0SMjWIQv4OAzoP7WGB+Zq6IiEMoDsyd5lLEyDMbLG8WRXfO70bElmVZz4qI/uqWcxHwHxGxSxSDEn++n7ar1nQM8Oq6u2MAd1G0St08IvYql+vObBqM/940sH9cBHwyInYtx0joqTXpWIru2wsjYhe80FYXynOmk4EfRsRh5fnSBIpYm0lxEn4XcEREbBsRO1KM2Virfh+4GHhDFI+0Hk0xbljt+W1P52HnAx+MiIPKm2xfB24tuwdtICJeWLam3YQi+bUCz1u0ESJi3yge2LNr+Xk3iu4/twC/AD4bES+Iwl6d5/1duA1YHMXg3ZtF8aCFA+Lpx7qPpTj/XxIR+wIfH9hvpnbRSwyfD/xnFANjb0FxjL2wrpfOieX5z3Moxva9sGbeCyLirWXr1k9RXGPeQnHNkBTXBUTxoKuGHppQ3uSbBJwcEaMj4qUUY1F2zr8GuJqiR9ALohgEf2wUD+35UC+b/zVFa9bVmbnBA1damUmlfpCZ3wU+TTHw41yKuwXHAb8DvkYRuHcD9wB/K6c1qnM8mWszs7ZZ+A8oWnNcFRGLKXawF/WwnR0pTrwWUXSVuwE4OzMXA5+kOKFbQHEBP7Hmuz1Y1mFq2bywtkkimTmZ4o70Dymarb+RYgDNVQ18t70pssFLKO5e/jgzr2tgPQ1jmXkaxf7yOYqLg9kUXW4+T5GMPBY4pYzrL1PEZue6yygG0765jMcXN1Dk+yiSp/dTxPjFNNastRE/p7gov5tiQOTLKO7ArO1pJbWnLMaum9TFrO9T3N2aTdF8+tweNnMmsH8Z/7/rh2r1tH/8nKLb9N8pfrvqW1jVOplisPqFwKW9LKs2Vv4GfJGihfQi4FaK86ZDy64CZ1PE3DSK4+uFdZv4BkWS6KmI+Gw5/ssnKG7CzaKI45k1y3d7HlZePJxI0WJ7FkWrkNox9+ptSbFfLKBoST6Poiu/1FeLKc7fb42IpRTn8/cCn8nM31Cc85xXLvc7igGLN1B2cX4DxZiPj1Cck/+CYhBjgM9SnOMvpojh+v1K6qtuYxj4JcUx/UaKuFxB8bCpWjdQDIfyJ+A7mXlVzbzfU4zfu4CiS9lby9439wPfpbh+nA0cCNxcoc7vLus8H/gKGw5L8HaKc/oLKc5r7qV4YMk1vWz3bIrkVuWHsQx3kY6LLEn9omzp99PM7O5OoiRJkqQWExGbUTxV/fmZ+XCz6zOYbKkkSX1UNjE/omwauwvF3Y5Lml0vSZIkSYPq48Dt7ZZQAlsqSVKflQPC3kDxeOnlFN1+/qN8vKokSZKkFhcR0ygGCn9zZt7Z5OoMOpNKkiRJkiRJqszub5IkSZIkSarMpJIkSZIkSZIqG9XsClQxbty4nDBhQrOroTZ0xx13PJmZ45tVvrGvZjH21c6Mf7UrY1/tythXO+tr/A+rpNKECROYNGlSs6uhNhQR05tZvrGvZjH21c6Mf7UrY1/tythXO+tr/Nv9TZIkSZIkSZWZVJIkSZIkSVJlLZVUykxWrelodjUkSZIkSZJaXksllb55+YPs86XLWbF6bbOrIkmSJEmS1NJaKql0we0zAEwqSZIkSZIkDbCWSipJkiRJkiRpcJhUkiRJkiRJUmUmlSRJkiRJklSZSSVJkiRJkiRV1pJJpcxm10CSJEmSJKm1tVRSKaLZNZAkSZIkSWoPLZVU6mRDJUmSJEmSpIHVUkklGypJkiRJkiQNjpZKKkmSJEmSJGlwmFSSJEmSJElSZSaVJEmSJEmSVFlLJpUyHapbkiRJkiRpILVUUinCobolSZIkSZIGQ0sllSRJkiRJkjQ4WjKpZOc3SZIkSZKkgdVSSSU7v0mSJEmSJA2OlkoqSZIkSZIkaXC0ZFLJh79JkiRJkiQNrJZKKvnwN0mSJEmSpMHRUkklSZIkSZIkDQ6TSpIkSZIkSarMpJIkSZIkSZIqa8mkUuJI3ZIkSZKetmjFan74p4fp6PBaQZL6S4sllcqRuv2dkCRJklTjlD/cz3evfohrHpjd7KpIUstoqaSST3+TJEmS1JXbp80HYPVa70BLUn9pqaSSJEmSJNWbu3gl0+cta3Y1JKnlmFSSJEmS1NKWrlyz7r29GySp/5hUkiRJkiRJUmUmlSRJkiRJklRZSyaVHHpPkiRJUievDyRpYLRUUqmze3T6qyFJkiRJkjSgWiup5KB7kiRJkiRJg6KlkkqSJEmS1BPvQ0tS/zGpJEmSJEmSpMpMKkmSJElqaVkz6KpDZkhS/zGpJEmSJEmSpMpaMqmUPjRUkiRJkiRpQLVUUikcdk+SJEmSJGlQtFRSqVPaUEmSJElSycsDSRoYLZVUctA9SZIkSfXSu86SNCBaKqkkSZIkSfVue2RBzSfvREtSfzGpJEmSJKml3fyPJ5tdBUlqSS2ZVLJxqyRJkqSuOGSGJPWflkoq+fsgSZIkaQM1d50dXkmS+k9LJZUkSZIkqd6l98xqdhUkqSWZVJIkSZIkSVJlLZlU8pGhkiRJkiRJA6ulkkrhqHuSJEmSJEmDoqWSSp1sqCRJkiRJkjSwWjKpJEmSJEmSpIFlUkmSJEmSJEmVmVSSJEmS1DaWr17T7CpIUsswqSRJkiSpbYzw4T6S1G9MKkmSJEmSJKmylkoqedNBkiRJkiRpcLRkUimzufWQJEmSNDSFd6Ilqd+0VFJJkiRJkmrd+NDc9T4/tWxVk2oiSa3HpJIkSZKklvW+X9623ucv//6+JtVEklqPSSVJkiRJkoaJqXOX8PcZTzW7GhIAo5pdAUmSJEmS1JhXf/cGAKZ98/VNrolkSyVJkiRJkiT1QUsmlRIf/yZJkiRJkjSQWiqpNHfxSgAemLW4yTWRJEmSJElqbS2VVFqxugOA71/9UJNrIkmSJEmS1NpaKqnUafJsWypJkiRJkiQNpJZMKkmSJEmSJGlgmVSSJEmSJElSZSaVJEmSJEmSVJlJJUmSJEmSJFVmUkmSJEmSJEmVmVSSJEmSJElSZSaVJEmSJEmSVJlJJUmSJEmSJFVmUkmSJEmSJEmVmVSSJEmSJElSZSaVJEmSJEmSVNmoZlegP/zpgdlstsnIZldDkiRJkiSpbbREUul7Vz/ETltt2uxqSJIkSZIktQ27v0mSJElSD55YuIJr7p/d7GpI0pDTMkmlGfOXN7sKkiRJklrQW358Mx/+9aRmV0OShpyWSSpNnr242VWQJEmS1IJmLVzR7CpIDfnEuX/jB9c83OxqqI20TFJJkiRJkgZSR0c2uwpSjy69Zxbfv+ahZldDbcSkkiRJkiQ14IaH5za7CpI0pJhUkiRJkqQGrFlrSyVJqmVSSZIkSZIakGlSSZJqmVSSJEmSpAasdUwlDTGZ2WVcrlnbYRJUg8KkkiRJkiR1Y9WajnXvV6xZ28SaSBv6yQ3/4FlfvIzp85auN32vEy7nzJseaVKt1E5MKkmSJElSjSlzlrD/l69gxvxlnHfr9HXTZy1c0cRaSRs67YrJAHzu4rs3mPfbvz022NVRG2qJpFJEs2sgSZIkqVVcNGkGy1at5dJ7ZnHSH+5fN73zAl4aam59ZP4G0ybPXtyEmqjdtERSSZIkSZL6S2eXt+nzljW5JlLfOQaYBoNJJUmSJEmqcek9swA4/7ZHm1wTaX1r1nb0vpA0iEwqSZIkSVINR9fQUDV/2apmV0FaT0skle59bFGzqyBJkiRpiFltqw61mI5+COmv/vF+Hnlyae8LSg1oiaRSV0645B4edmAySZIkqW11jo1UVU8j0dzw0Ny+VUbqB2s2Mqt0z8yFnHnTI7zqO9f3T4XU9lo2qXTurY/yhh/e1OxqSJIk9auZC5bx0V9PYvmqtc2uijTkzVm8ssvpvbVgmtvNegAPzLKXhJpn2UYe+xevXL3ufaYDeWvjtWxSCWBlH+9MSJIkDVUnTbyPq+6fzZ8enN3sqkhD3iV3Ptbl9EXLV3c5vRHfvPzBPq8rbazFK9ase9+XpFDtE+Hue9wEqTZeSyeVJEmSWs01D8wBwBvMUs/mLVnJ6X96uMt5T21EUklqptqk0Oq11X8I5i15eqDvGfOX9Uud1N5aOqm045abNrsKkiS1lcUrVnPH9AXNrkZbuOexhc2ugjSkveOnf+12nmOvarhaU9N1c+LfH19vXkdH70mmT11417r3Hz/3b/1XMbWtlk4qracQzX4AABuiSURBVGlgp5IkSf3nY+fcwdt+8heWrVrT+8LaKDdMdrBgqSdTe3i6lQ+F03BVe4375JL1x/5a1UtgL13pb7P6X0snlep3MkmSNLDunlm0nlm9xhs7A211fzxXWmpTa+0/qmHqoZpWdtPnrd997T8uuHOD5WvHXZq1cMXAVUxtq6WTSlKr+82kGbzjp39pqKmrJA2GKP/NHh/Irf4wdW73rTAk9ay7c6f5S1dxyZ0ze11/8QrHZFJzfO3SB9a9X1t3c+HK+zZ8gMP8pas2mCb1J5NK0jA2a+EKbp+2gI7yDkRmcuLv7uW+xx1nQ1JzjBhRpJVsBCCpGe58dAFzFvXeGmNtN0mlj519B/954d97Xf+gU66uXDepv61pYKDuGQuWr3v/zcsf6GFJqW9MKknD2Mjy4q0jYdGK1Ux9ciln3zKd9//ytibXTFK76myp1GFWSdIgW7h8NW/58V845Ot/6nXZ7rq/3TZtfkNldZeUkgbT1Q9s2DKpXu1DHTqfHir1p1HNrsBA+/PDc1m1poND99uh2VWR+l2UV28dmfzTSVetm/7kEpu5SmqOKA9MXm5JGmzzasZT/ekN/+hx2bmLNxx79aaHn+z3Okn96dG6MZQWr+h94O0Tf3cvR794j27nL1m5hi3GFGmBjo7klqnzWL56rdfPaljLt1Q6+szbOOasSc2uhjQgRkZnSyUv3yQNDevGVPKwNChWd/Okn4XLHO9F7eeK+55Y9/6blz/Y47LfvnIy5946fb0WR+8989ZK5d356IJqFZQ20uf/7+4+rffzG6fy2FPLu5x35b1P7zcv/safePcvbvX6WZW0fFKp04rVa/nj3Y83uxpSvxpRJpUWLd/wLsUd04sTncx0IG9Jg+bplkoed5rlottn8NxTrmLyE4t7X1hqIaddMbnS8idcci/P+uJlzJi/rE+PWrdluAbbVptt0qf1Tr3sAf7lm9d2Oe8zv3l6DLE5XbTgk3rTNkmlfU+8guPOu5M7ps9n6co1rFnbwZq1Haxa08GfHpi9QVPC2YtWdNkstr+tXtvBslXVf8QkeLr724u/seHYAW/7yV9YuWYth//gzzzzi5fx9xlPDXLtpIH1xMIVHHTKVXzs7DuaXRXV6Dwu2VJpcNwweS5Q7A8Tjr+UK+59gj89WIyxMXXukmZWTRo085as7LVlUk9edtp1POcrV1Zeb9NN2uZSSkNEbWu8/jZlzvq/Gd21bJLqtfyYSvUWLl/Nc75yJZuMDJ6/+zbc+sjTg/FN/foRrFrbwaabjORF5QB/0775+j6V88TCFWw/dsy6p+AsWLqKVWs72GLMKB6dv4z9dtqSaU8u5ZXfuX6jylF76xyouzvP/tIV694fecbNAPzhuJdy4K5bDWi9pMHQmUwdyBMsVWf3t8H14V9PYtdtNmOP7TYH4GPn3MGr990egE1GesGr9vCCr13TlHLPveVRXrb3+KaULfWnmx5+coPun//yzWt55BtHrGuBLHWn7ZJKH/pV0T909dpcL6EE8MwvXgbAjf/1qh63MeH4SwHYfdvN2WqzTRgxIthr/Bb8399m9rlendt8xT7jOXS/7blrxlM88uRSvvfOg/jCb+/mlqnzmfr1I9YlqSR4uvtbFW/80U0AnHDEfpx62fqPFf3amw/gvT0M5CcNVROOv5SRI4K/HP9qdthyU+YuXklmctZfp/HJQ/dmzKiRza5i28h1/5pVGiwzFyxnZs0jo699sHi6zwOzFvHqfbdfd8NMGu4WLlvNR349ia+8aX922Xoztt58NDMXLOt9xQHiTQ21iu7GEzv8B3/m5+87mJeddh377bQlv//EvzB6lDcstL62Syo14uXfvm7d+85kT1cenf/0j1h/dS264aG53PDQ3HWfX1W2ZIKnk15d+cNxL2W7LUYzZtQINh89ihEjikedBsHIEcHqtR1stslIIoq7x90lp9Z2JCOiGBMjy9vMZqeHro3JMdYnlAC+9Lt7+dLv7u1xvVEjgmeOfwbjthjDzltvxj47bMGj85fxucP2ZctN+9bPW6pq2pNLN5i2tiPXtTKtdcZ1xROA/nDcS3nW9s9g9dpk89Ej17Xi6OjIIZOwX9uRzFuykm2fMZpRXbQymbVwOTuM3ZRVazuY/MRinrvb1k2oZfc6OnJd1/E7H32KnQ7crMk1am/fvfohvnv1QxtM//tXXsfv73qM8VuM4fADd+Ifc5ew5aabMG6L0fzPjVN51wt3Z6vNqx3Pu9qPhuN5xLQnl7LjVpuahBuinntK8aTb159+U5NrIg2+t/z45kEv88EnFvOy04pr4wdmLWKfL13OPSe9jjGjRppc0jomlVpEZ+uTVrLL1ptV7su7x3abM7qPzf1fs/8OfP6wffu0brOc+Pv7Br3MNR3JQ7OX8NDs9ftdn3PLo+ve77vj2MGuljbCZqNHcsmx/9LsalTSW9fPrgyl4+QuW2/G2o5kbTmQ/pqOZOHy1npa17Hn/m1Qy9tnhy02OC51Tq8VrB8733jbgTx/920GtG5DzXNPvqrH+RszNo02zt7bb8HDc/p3LKz6faDTkQftwidetVe/ljXUXfbJl3HkGTexem3/taSccPylQ/q8p5W7Iie53jG9s4VsV9NqjR87hnM//OKBr2A/mjJnMXc+OjTGRz3wpOI3ZI/tNmdNuS9tPnpkl+dmtfHXyP2F3uK19v8ziIa2qfWd/q7nsc8O/XvMaomk0hv+aSf+ePcs3nnwrhw8YVs+d/HdvOGfdiKB2x6ZPygDbqv/HbT71pWTSvvvtGWfDy47jB3TtxWb6KwPHcL7f3lbs6uxnvFjx6wb20PDw3C8I7/rNsO3Bczzd9+aPcdtwcgRRXJs5IhgZAS3PjKfB4fx07pesc/49VraDrZnjtuCLTfdhEnTn37E9747jmXPcc9Y97mrk9XNhmH8v2jPbTfowj/cPHuHsUyePXzjfSDsus1m7L1D/yaVth87hmeN7zqptN0zRvdbOYPl4o+9hLf/9K89LrPX9ltw5HN35pxbp/P1txzIbtsWNxw7W6BN/urhPbb+33v7Lfj+vx3EslVreeGEbZi3dBVLV65h5oLl7LjVpowZNYKf3ziVs/46HYDX7b/DkL+wrU+m96eukjYDWV5tuUF0m0jqnFc7vfP/aevNh1/sjxqx/k3z2044lMP++8/MX1o8gfD0dz2PT55/J6NHjeDzh+3LubdO56Ddtua3f3usy+1dcuw/M2fxSv7fRjzsZO/tx/LEouUEwbgtRnfbcqn2/6kRvcVPZ88bu9n3TV8bYPQkchilrw8++OCcNGlSs6uhNhQRd2Tmwc0q39hXsxj7amfGv9qVsa92ZeyrnfU1/u0IKUmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqzKSSJEmSJEmSKhtWA3VHxFxgerProba0R2aOb1bhxr6ayNhXOzP+1a6MfbUrY1/trE/xP6ySSpIkSZIkSRoa7P4mSZIkSZKkykwqSZIkSZIkqTKTSpIkSZIkSarMpJIkSZIkSZIqM6kkSZIkSZKkykwqSZIkSZIkqTKTSpIkSZIkSarMpJIkSZIkSZIqM6kkSZIkSZKkykwqSZIkSZIkqTKTSpIkSZIkSarMpJIkSZIkSZIqM6kkSZIkSZKkykwqSZIkSZIkqTKTSpIkSZIkSarMpJIkSZIkSZIqM6kkSZIkSZKkykwqSZIkSZIkqTKTSpIkSZIkSarMpJIkSZIkSZIqM6kkSZIkSZKkykwqSZIkSZIkqbJRza5AFePGjcsJEyY0uxpqQ3fccceTmTm+WeUb+2oWY1/tzPhXuzL21a6MfbWzvsb/sEoqTZgwgUmTJjW7GmpDETG9meUb+2oWY1/tzPhXuzL21a6MfbWzvsa/3d8kSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlDSWVIuKwiJgcEVMi4vgu5o+JiAvL+bdGxIRy+nYRcV1ELImIH9Wtc325zbvK1/b98YUkSZIkSZI08Eb1tkBEjATOAF4LzARuj4iJmXl/zWLHAAsyc6+IOAr4FvBvwArgROCA8lXvPZk5aSO/gyRJkiRJkgZZIy2VDgGmZObUzFwFXAAcWbfMkcBZ5fuLgUMjIjJzaWbeRJFckiRJkiRJUotoJKm0CzCj5vPMclqXy2TmGmAhsF0D2/7fsuvbiRERDSwvSZIkSZKkIaCZA3W/JzMPBF5Wvo7uaqGI+GhETIqISXPnzh3UCkrNZOyrXRn7amfGv9qVsa92ZexruGskqfQYsFvN513LaV0uExGjgK2AeT1tNDMfK/9dDJxH0c2uq+V+lpkHZ+bB48ePb6C6Umsw9tWujH21M+Nf7crYV7sy9jXcNZJUuh3YOyL2jIjRwFHAxLplJgLvL9+/Hbg2M7O7DUbEqIgYV77fBHgDcG/VykuSJEmSJKk5en36W2auiYjjgCuBkcAvM/O+iDgFmJSZE4EzgbMjYgownyLxBEBETAO2BEZHxJuB1wHTgSvLhNJI4Brg5/36zSRJkiRJkjRgek0qAWTmZcBlddO+XPN+BfCObtad0M1mX9BYFSVJkiRJkjTUNHOgbkmSJEmSJA1TJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlJpUkSZIkSZJUmUklSZIkSZIkVWZSSZIkSZIkSZWZVJIkSZIkSVJlDSWVIuKwiJgcEVMi4vgu5o+JiAvL+bdGxIRy+nYRcV1ELImIH9Wt84KIuKdc5/SIiP74QpIkSZIkSRp4vSaVImIkcAZwOLA/8K6I2L9usWOABZm5F/B94Fvl9BXAicBnu9j0T4CPAHuXr8P68gUkSZIkSZI0+BppqXQIMCUzp2bmKuAC4Mi6ZY4EzirfXwwcGhGRmUsz8yaK5NI6EbETsGVm3pKZCfwaePPGfBFJkiRJkiQNnkaSSrsAM2o+zyyndblMZq4BFgLb9bLNmb1sU5IkSZIkSUPUkB+oOyI+GhGTImLS3Llzm10dadAY+2pXxr7amfGvdmXsq10Z+xruGkkqPQbsVvN513Jal8tExChgK2BeL9vctZdtApCZP8vMgzPz4PHjxzdQXak1GPtqV8a+2pnxr3Zl7KtdGfsa7hpJKt0O7B0Re0bEaOAoYGLdMhOB95fv3w5cW46V1KXMnAUsiogXl099ex/w+8q1lyRJkiRJUlOM6m2BzFwTEccBVwIjgV9m5n0RcQowKTMnAmcCZ0fEFGA+ReIJgIiYBmwJjI6INwOvy8z7gWOBXwGbAZeXL0mSJEmSJA0DvSaVADLzMuCyumlfrnm/AnhHN+tO6Gb6JOCARisqSZIkSZKkoWPID9QtSZIkSZKkocekkiRJkiRJkiozqSRJkiRJkqTKTCpJkiRJkiSpMpNKkiRJkiRJqsykkiRJkiRJkiozqSRJkiRJkqTKTCpJkiRJkiSpMpNKkiRJkiRJqsykkiRJkiRJkiozqSRJkiRJkqTKTCpJkiRJkiSpMpNKkiRJkiRJqsykkiRJkiRJkiozqSRJkiRJkqTKTCpJkiRJkiSpMpNKkiRJkiRJqsykkiRJkiRJkiozqSRJkiRJkqTKTCpJkiRJkiSpMpNKkiRJkiRJqsykkiRJkiRJkiozqSRJkiRJkqTKTCpJkiRJkiSpsoaSShFxWERMjogpEXF8F/PHRMSF5fxbI2JCzbwvlNMnR8S/1kyfFhH3RMRdETGpP76MJEmSJEmSBseo3haIiJHAGcBrgZnA7RExMTPvr1nsGGBBZu4VEUcB3wL+LSL2B44CngPsDFwTEftk5tpyvVdl5pP9+H0kSZIkSZI0CBppqXQIMCUzp2bmKuAC4Mi6ZY4EzirfXwwcGhFRTr8gM1dm5iPAlHJ7kiRJkiRJGsYaSSrtAsyo+TyznNblMpm5BlgIbNfLuglcFRF3RMRHq1ddkiRJkiRJzdLMgbpfmpnPBw4HPhERL+9qoYj4aERMiohJc+fOHdwaSk1k7KtdGftqZ8a/2pWxr3Zl7Gu4aySp9BiwW83nXctpXS4TEaOArYB5Pa2bmZ3/zgEuoZtucZn5s8w8ODMPHj9+fAPVlVqDsa92ZeyrnRn/alfGvtqVsa/hrpGk0u3A3hGxZ0SMphh4e2LdMhOB95fv3w5cm5lZTj+qfDrcnsDewG0R8YyIGAsQEc8AXgfcu/FfR5IkSZIkSYOh16e/ZeaaiDgOuBIYCfwyM++LiFOASZk5ETgTODsipgDzKRJPlMtdBNwPrAE+kZlrI2IH4JJiLG9GAedl5hUD8P0kSZIkSZI0AHpNKgFk5mXAZXXTvlzzfgXwjm7WPRU4tW7aVOC5VSsrSZIkSZKkoaGZA3VLkiRJkiRpmDKpJEmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqzKSSJEmSJEmSKjOpJEmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqzKSSJEmSJEmSKjOpJEmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqzKSSJEmSJEmSKjOpJEmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqzKSSJEmSJEmSKjOpJEmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqzKSSJEmSJEmSKjOpJEmSJEmSpMpMKkmSJEmSJKkyk0qSJEmSJEmqrKGkUkQcFhGTI2JKRBzfxfwxEXFhOf/WiJhQM+8L5fTJEfGvjW5TkiRJkiRJQ1evSaWIGAmcARwO7A+8KyL2r1vsGGBBZu4FfB/4Vrnu/sBRwHOAw4AfR8TIBrcpSZIkSZKkIaqRlkqHAFMyc2pmrgIuAI6sW+ZI4Kzy/cXAoRER5fQLMnNlZj4CTCm318g2JUmSJEmSNEQ1klTaBZhR83lmOa3LZTJzDbAQ2K6HdRvZpiRJkiRJkoaoIT9Qd0R8NCImRcSkuXPnNrs60qAx9tWujH21M+Nf7crYV7sy9jXcNZJUegzYrebzruW0LpeJiFHAVsC8HtZtZJsAZObPMvPgzDx4/PjxDVRXag3GvtqVsa92ZvyrXRn7alfGvoa7RpJKtwN7R8SeETGaYuDtiXXLTATeX75/O3BtZmY5/ajy6XB7AnsDtzW4TUmSJEmSJA1Ro3pbIDPXRMRxwJXASOCXmXlfRJwCTMrMicCZwNkRMQWYT5EkolzuIuB+YA3wicxcC9DVNvv/60mSJEmSJGkg9JpUAsjMy4DL6qZ9ueb9CuAd3ax7KnBqI9uUJEmSJEnS8DDkB+qWJEmSJEnS0BPF0EfDQ0QsBiY3sQrjgCfbsGzLh2dn5thmFd7msW/5zS3f2G/f/3vLN/4972nf8o399v7/b+fyjf32/b+3/D7Gf0Pd34aQyZl5cLMKj4hJzSq/mWVbflF+s8outW3sW37zjz3NKLeGsW/5HvubpNnHnnb97kOl/GaVXWrb2Lf85h97mlFuDWPf8ofdsd/ub5IkSZIkSarMpJIkSZIkSZIqG25JpZ+1cfnt/N0t3/Itvz3LtnzLt/z2Lb+dv7vlW77lt2fZlm/5w7L8YTVQtyRJkiRJkoaG4dZSSZIkSZIkSUPAkEsqRcRhETE5IqZExPFdzB8TEReW82+NiAmDXP6nI+L+iLg7Iv4UEXsMZvk1y70tIjIi+nV0+EbKj4h3ln+D+yLivMEsPyJ2j4jrIuLO8v/giH4s+5cRMSci7u1mfkTE6WXd7o6I5/dX2TVlGP9Niv92jv1y+02Nf2PfY3+7HvuNfWO/XWO/LKNt49/Y97ynXWO/kfJrljP+h8OxPzOHzAsYCfwDeCYwGvg7sH/dMscCPy3fHwVcOMjlvwrYvHz/8cEuv1xuLHAjcAtw8CB//72BO4Ftys/bD3L5PwM+Xr7fH5jWj+W/HHg+cG83848ALgcCeDFwa3+VXeH7G/8DEP/tHvvlNpsW/8a+x/5mxr+xb+wb+573DHb8G/ue97Rr7Ddafrmc8Z/D49g/1FoqHQJMycypmbkKuAA4sm6ZI4GzyvcXA4dGRAxW+Zl5XWYuKz/eAuzaT2U3VH7pq8C3gBX9WHaj5X8EOCMzFwBk5pxBLj+BLcv3WwGP91fhmXkjML+HRY4Efp2FW4CtI2Kn/iof47+Z8d/WsQ9Nj39j32N/ux77jX1jv11jH9o7/o19z3vaNfYbKr9k/BeG/LF/qCWVdgFm1HyeWU7rcpnMXAMsBLYbxPJrHUORxesvvZZfNj/bLTMv7cdyGy4f2AfYJyJujohbIuKwQS7/JOC9ETETuAz4934svzdV42Mgtm/8D0z8G/u9G8j4N/Y99g/l+Df2n2bsG/ue9wxS2ca+5z20Zuw3VL7xP7yO/aMGtDotLCLeCxwMvGIQyxwBfA/4wGCV2YVRFM0BX0mRsb4xIg7MzKcGqfx3Ab/KzO9GxEuAsyPigMzsGKTyRdvGv7Gvdo19MP7bnrFv7LezwY5/Yx8w9ocEj/3GfyOGWkulx4Ddaj7vWk7rcpmIGEXRHGzeIJZPRLwGOAF4U2au7KeyGyl/LHAAcH1ETKPo4zixHwcua+T7zwQmZubqzHwEeIhihxus8o8BLgLIzL8CmwLj+qn83jQUHwO8feN/YOLf2O/dQMa/se+xfyjHv7Fv7Bv7Bc97+i/+jf2hHfvgsd9jf/vGf/XYz34a8Kk/XhQZwanAnjw9aNVz6pb5BOsPWnbRIJf/PIqBtfZuxvevW/56+nfQska+/2HAWeX7cRRN47YbxPIvBz5Qvt+Pon9p9OPfYALdD1r2etYftOy2wf7/N/4HJv6N/ebGv7Hvsb/Z8W/sG/vG/uDGfoXv35Lxb+w3P/bL7TYl/ts59hstv25543+IH/v7NUD66QseQZEJ/AdwQjntFIoMKRRZut8AU4DbgGcOcvnXALOBu8rXxMEsv27Zft3BGvz+QdEc8X7gHuCoQS5/f+Dmcue7C3hdP5Z9PjALWE2RnT4G+BjwsZrvfkZZt3v6+29v/Dc3/ts59odC/P//du7QBoAQAIJg6L9pDAWwCv6Z8bgNISfQvrv/VP/a1772vXtO9K99755X29f//+7+sQ4CAAAAwLbb/lQCAAAA4AOMSgAAAABkRiUAAAAAMqMSAAAAAJlRCQAAAIDMqAQAAABAZlQCAAAAIDMqAQAAAJBNAnwu/5HX04UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x360 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x360 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_signals(signals)\n",
    "plt.show()\n",
    "\n",
    "plot_fft(fft)\n",
    "plt.show()\n",
    "\n",
    "plot_fbank(filter_banks)\n",
    "plt.show()\n",
    "\n",
    "plot_mfccs(mfcc_dict)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 326/326 [02:00<00:00,  4.20it/s]\n"
     ]
    }
   ],
   "source": [
    "if len(os.listdir('DataClean'))==0:\n",
    "    \n",
    "    for f in tqdm(df.audiofile):\n",
    "        signal,rate=librosa.load('data/'+f,sr=16000)\n",
    "        mask=envolope(signal,rate,0.0005)\n",
    "        wavfile.write(filename='DataClean/'+f,rate=rate,data=signal[mask])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}