sandbox_audio_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jab464/miniconda3/envs/pyannote/lib/python3.8/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: dlopen(/Users/jab464/miniconda3/envs/pyannote/lib/python3.8/site-packages/torchvision/image.so, 0x0006): Symbol not found: __ZN3c106detail19maybe_wrap_dim_slowExxb\n",
      "  Referenced from: /Users/jab464/miniconda3/envs/pyannote/lib/python3.8/site-packages/torchvision/image.so\n",
      "  Expected in: /Users/jab464/miniconda3/envs/pyannote/lib/python3.8/site-packages/torch/lib/libc10.dylib\n",
      "  warn(f\"Failed to load image Python extension: {e}\")\n"
     ]
    }
   ],
   "source": [
    "import parselmouth\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "from pydub import AudioSegment\n",
    "from pydub.playback import play\n",
    "\n",
    "import math\n",
    "\n",
    "import time\n",
    "\n",
    "#Danish you can comment this one\n",
    "from pyannote.audio import Pipeline\n",
    "\n",
    "#import set of functions I made for the automatic analysis of the audios\n",
    "import sys\n",
    "\n",
    "#here the path needs to be changed to your own local path\n",
    "sys.path.insert(1, '/Users/jab464/Documents/Github/EMBRACE-data-analysis/')\n",
    "from audio_analysis_functions import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "#Audio ASU mom-child\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par007_record-673758082.558921.wav'\n",
    "\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par007_record-673758082.558921_reduced_noise.wav'\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/mom-child-62'\n",
    "\n",
    "#Audio dad-child (Pittsburgh)\n",
    "#filename='../EMBRACE-data-analysis/audios/record-667269360.9571331.wav'\n",
    "#filename='../EMBRACE-data-analysis/audios/record-667269360.9571331_reduced_noise.wav'\n",
    "\n",
    "#Audio mom-grandma-child (Pittsburgh)\n",
    "#filename = '../EMBRACE-data-analysis/audios/record-672279722.51811.wav'\n",
    "\n",
    "#ASU par001\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par001-record-656468528.8997459_silence_removed.wav'\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par001-record-656468528.8997459.wav'\n",
    "\n",
    "#ASU par010 (with Sindhu there) DO NOT USE\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par010-record-691979477.209939.wav'\n",
    "\n",
    "#ASU par102\n",
    "#filename = \"../EMBRACE-data-analysis/audios/asu/par102-record-666060012.245397.wav\"\n",
    "\n",
    "#ASU par003\n",
    "#filename = \"../EMBRACE-data-analysis/audios/asu/par003-record-674009351.193422.wav\"\n",
    "\n",
    "#short test audio\n",
    "#filename = \"../EMBRACE-data-analysis/data/two_speakers.wav\"\n",
    "\n",
    "#Pitt 2023 study with families\n",
    "#filename = \"../EMBRACE-data-analysis/audios/summer23-pitt/18_voice-recordings/voice-recording-1684538821337-1684538952706.mp3\"\n",
    "\n",
    "#Summer 23 data sample\n",
    "filename =\"../EMBRACE-data-analysis/data/summer23-pitt/Family_41/41_Chromebook Data/41_voice-recordings/voice-recording-1686527367557-1686527501435.mp3\"\n",
    "\n",
    "#overlap test audio\n",
    "filename_overlap = \"../EMBRACE-data-analysis/audios/overlap.wav\"\n",
    "\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "get_voice_activity() takes 3 positional arguments but 4 were given",
     "output_type": "error",
     "traceback": [
      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[0;31mTypeError\u001B[0m                                 Traceback (most recent call last)",
      "Cell \u001B[0;32mIn[3], line 2\u001B[0m\n\u001B[1;32m      1\u001B[0m \u001B[38;5;66;03m#Get active voice segments\u001B[39;00m\n\u001B[0;32m----> 2\u001B[0m active_voice_segments \u001B[38;5;241m=\u001B[39m \u001B[43mget_voice_activity\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfilename\u001B[49m\u001B[43m,\u001B[49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m,\u001B[49m\u001B[38;5;28;43;01mFalse\u001B[39;49;00m\u001B[43m,\u001B[49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m)\u001B[49m\n\u001B[1;32m      4\u001B[0m \u001B[38;5;66;03m#Calculate total time voice\u001B[39;00m\n\u001B[1;32m      5\u001B[0m total_time_voice \u001B[38;5;241m=\u001B[39m \u001B[38;5;241m0\u001B[39m\n",
      "\u001B[0;31mTypeError\u001B[0m: get_voice_activity() takes 3 positional arguments but 4 were given"
     ]
    }
   ],
   "source": [
    "#Get active voice segments\n",
    "active_voice_segments = get_voice_activity(filename,True,False,True)\n",
    "\n",
    "#Calculate total time voice\n",
    "total_time_voice = 0\n",
    "counter = 0\n",
    "for segment in active_voice_segments:\n",
    "    start = segment[0]\n",
    "    end = segment[1]\n",
    "    time_duration = end-start\n",
    "    print(segment)\n",
    "    print(\"Duration segment \"+str(counter)+\": \"+str(time_duration)+\" secs.\")\n",
    "    total_time_voice = total_time_voice + time_duration\n",
    "    counter = counter + 1\n",
    "print(\"Total time active voice: \"+str(total_time_voice)+\" secs.\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "sns.set() # Use seaborn's default style to make attractive graphs\n",
    "plt.rcParams['figure.dpi'] = 200 # Show nicely large images in this notebook"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [],
   "source": [
    "#Load audio\n",
    "snd = parselmouth.Sound(filename)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1280x960 with 1 Axes>",
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(snd.xs(), snd.values.T)\n",
    "plt.xlim([snd.xmin, snd.xmax])\n",
    "plt.xlabel(\"time [s]\")\n",
    "plt.ylabel(\"amplitude\")\n",
    "plt.show() # or plt.savefig(\"sound.png\"), or plt.savefig(\"sound.pdf\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1280x960 with 1 Axes>",
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Remove noise from the audio\n",
    "#snd = parselmouth.praat.call(snd, \"Remove noise\", 0.0, 0.0, 0.025, 80.0, 10000.0, 40.0, \"Spectral subtraction\")\n",
    "\n",
    "pitch = snd.to_pitch()\n",
    "pitch_values = pitch.selected_array['frequency']\n",
    "pitch_values[pitch_values==0] = np.nan\n",
    "plt.plot(pitch.xs(), pitch_values, 'o', markersize=2)\n",
    "plt.show()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#MFCC coefficients\n",
    "mfcc_coefs = snd.to_mfcc()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Classify small chunks into the identity of the speaker\n",
    "audio = AudioSegment.from_wav(filename)\n",
    "\n",
    "voice_activity = get_voice_activity(filename,False,False,False)\n",
    "custom_size_voice_activity = custom_size_segments(voice_activity)\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#manual labeling of the voice segments\n",
    "#child=c\n",
    "#robot male english = rme\n",
    "#robot male spanish = rms\n",
    "#robot female english = rfe\n",
    "#robot female spanish = rfs\n",
    "#adult male = am\n",
    "#adult female = af\n",
    "#(if additional adults number them)\n",
    "#adult male 2 = am2\n",
    "#adult female 2 = af2 ...\n",
    "#if they are talking simultaneously = A&B\n",
    "#if they are talking separately but sequentially = A,B\n",
    "\n",
    "labeling_file_str = \"\"\n",
    "starting_index = int(input(\"Which index would you like to start from? (type 0 if from the beginning or >0 if you want to continue labeling):\"))\n",
    "for i in range (starting_index,len(custom_size_voice_activity)):\n",
    "    active_segment = custom_size_voice_activity[i]\n",
    "#for active_segment in custom_size_voice_activity:\n",
    "    play_audio_segment(audio,active_segment[0]*1000,active_segment[1]*1000)\n",
    "    label = input(\"Enter label for this audio segment: \")\n",
    "    if(label==\"end\"):#stop tagging\n",
    "        break\n",
    "    while(label==\"r\"):#if you want the audio chunk to be repeated\n",
    "        play_audio_segment(audio,active_segment[0]*1000,active_segment[1]*1000)\n",
    "        label = input(\"Enter label for this audio segment: \")\n",
    "        if(label==\"end\"):\n",
    "            break\n",
    "    label_line = str(i)+\" \"+str(active_segment)+\" \"+label\n",
    "    labeling_file_str = labeling_file_str + label_line + \"\\n\"\n",
    "    print(str(i)+\" out of \"+str(len(custom_size_voice_activity)-1))\n",
    "if(starting_index==0):\n",
    "    f = open(filename+\"_labeled.txt\", \"w\")\n",
    "    f.write(labeling_file_str)\n",
    "    f.close()\n",
    "elif(starting_index<len(custom_size_voice_activity)):\n",
    "    f = open(filename+\"_labeled.txt\", \"a\")\n",
    "    f.write(labeling_file_str)\n",
    "    f.close()\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#for active_segment in custom_size_voice_activity:\n",
    "#first, get the labels from the file\n",
    "labels = []\n",
    "with open(filename+\"_labeled.txt\") as file:\n",
    "  labels=file.readlines()\n",
    "\n",
    "correct_predictions = 0\n",
    "correct_predictions_single_label = 0\n",
    "total_single_labels = 0\n",
    "for i in range(0,len(custom_size_voice_activity)):\n",
    "    label_str = labels[i]\n",
    "    label_str = label_str.replace(\", \",\",\")\n",
    "    label_info = label_str.split(\" \")\n",
    "    label = label_info[2]\n",
    "    active_segment = custom_size_voice_activity[i]\n",
    "    #print(active_segment)\n",
    "    #predicted_label_str = classify_audio_freq(avg_pitch(pitch,70,400,[active_segment]))\n",
    "    predicted_label_str = classify_audio_freq(median_pitch(pitch,60,500,active_segment))\n",
    "    q3 = quantile_pitch(pitch,0,1000,active_segment,75)\n",
    "    q1 = quantile_pitch(pitch,0,1000,active_segment,25)\n",
    "    iqr = q3-q1\n",
    "\n",
    "    tagged_label = label[:-1]\n",
    "    predicted_labels = predicted_label_str.split(\"|\")\n",
    "    correct_prediction = False\n",
    "    if('&' not in tagged_label) and (',' not in tagged_label):\n",
    "        total_single_labels = total_single_labels + 1\n",
    "    for predicted_label in predicted_labels:\n",
    "        if predicted_label in tagged_label:\n",
    "            correct_prediction = True\n",
    "            break\n",
    "    if correct_prediction:\n",
    "        correct_predictions = correct_predictions+1\n",
    "        if('&' not in tagged_label) and (',' not in tagged_label):\n",
    "            correct_predictions_single_label = correct_predictions_single_label + 1\n",
    "    else:\n",
    "        print(\"iqr: \"+str(iqr)+\" q1: \"+str(q1)+\" q3: \"+str(q3))\n",
    "        print(str(i)+\" \"+tagged_label+\" -> \"+predicted_label_str+ \" | Prediction: \"+str(correct_prediction))\n",
    "\n",
    "avg_accuracy = correct_predictions/len(custom_size_voice_activity)\n",
    "avg_accuracy_single_labels = correct_predictions_single_label/total_single_labels\n",
    "print(\"Avg accuracy: \"+str(avg_accuracy*100)+\"%\")\n",
    "print(\"Avg single labels: \"+str(avg_accuracy_single_labels*100)+\"%\")\n",
    "\n",
    "#play(audio)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "play_and_plot_audio_segment_by_index(audio,pitch,custom_size_voice_activity,67)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "#The average man’s speaking voice, for example, typically has a fundamental frequency between 85 Hz and 155 Hz. A woman’s speech range is about 165 Hz to 255 Hz, and a child’s voice typically ranges from 250 Hz to 300 Hz and higher.\n",
    "#https://www.axiomaudio.com/blog/audio-oddities-frequency-ranges-of-male-female-and-childrens-voices#:~:text=A%20woman's%20speech%20range%20is,to%20300%20Hz%20and%20higher.\n",
    "#for adult male\n",
    "#secs_pitch_adult,pitch_values_adult,index_pitch_values_adult = extract_pitch_segments(pitch,85,155)\n",
    "\n",
    "#for adult female\n",
    "secs_pitch_adult,pitch_values_adult,index_pitch_values_adult = extract_pitch_segments(pitch,165,255)\n",
    "\n",
    "#for the child\n",
    "secs_pitch_child,pitch_values_child,index_pitch_values_child = extract_pitch_segments(pitch,250,400)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "data": {
      "text/plain": "[(2.063489583333334, 4.373489583333335),\n (5.453489583333334, 6.073489583333334),\n (7.463489583333335, 8.053489583333334),\n (9.083489583333336, 14.873489583333335),\n (16.463489583333335, 16.923489583333332),\n (18.113489583333333, 20.063489583333332),\n (21.183489583333333, 21.553489583333334),\n (23.063489583333332, 24.923489583333335),\n (26.923489583333335, 29.763489583333335),\n (30.983489583333334, 31.783489583333335),\n (32.90348958333334, 33.29348958333334),\n (35.30348958333334, 36.45348958333334),\n (38.16348958333334, 40.09348958333334),\n (41.47348958333334, 41.90348958333334),\n (42.963489583333335, 51.33348958333334),\n (52.52348958333334, 53.86348958333334),\n (55.72348958333334, 61.15348958333334),\n (63.50348958333334, 64.21348958333333),\n (65.81348958333334, 67.72348958333333),\n (69.02348958333333, 72.13348958333333),\n (75.38348958333333, 76.37348958333334),\n (79.35348958333333, 80.87348958333334),\n (82.43348958333333, 83.68348958333333),\n (85.29348958333333, 86.76348958333332),\n (91.15348958333333, 92.42348958333334),\n (93.73348958333334, 94.69348958333333),\n (96.28348958333333, 97.67348958333334),\n (100.00348958333333, 101.74348958333333),\n (105.79348958333333, 107.81348958333334),\n (109.72348958333333, 110.02348958333333),\n (111.13348958333333, 111.37348958333334),\n (113.56348958333334, 120.69348958333333),\n (122.00348958333333, 125.31348958333334),\n (127.30348958333333, 127.44348958333333),\n (131.00348958333333, 132.91348958333336)]"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Generation of the time intervals where there is a significant participation of the child (>= .3 second)\n",
    "threshold_time_interval = 1\n",
    "tuples_pitch_times_child = []\n",
    "prev_sec = secs_pitch_child[0]\n",
    "curr_time_tuple = (secs_pitch_child[0],)\n",
    "for i in range(1,len(secs_pitch_child)):\n",
    "    next_sec = secs_pitch_child[i]\n",
    "    time_diff = next_sec - prev_sec\n",
    "    if time_diff>threshold_time_interval or i==(len(secs_pitch_child)-1):\n",
    "        curr_time_tuple+=(prev_sec,)\n",
    "        tuples_pitch_times_child.append(curr_time_tuple)\n",
    "        curr_time_tuple = (next_sec,)\n",
    "    prev_sec = next_sec\n",
    "secs_pitch_child\n",
    "tuples_pitch_times_child"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "[(2.4734895833333344, 3.193489583333334),\n (5.503489583333335, 6.033489583333334),\n (9.183489583333335, 10.533489583333335),\n (11.633489583333334, 15.633489583333336),\n (17.413489583333334, 27.673489583333335),\n (29.263489583333335, 32.86348958333334),\n (34.11348958333334, 34.80348958333334),\n (38.79348958333334, 40.283489583333335),\n (41.47348958333334, 43.27348958333334),\n (45.07348958333334, 45.07348958333334),\n (47.12348958333334, 48.033489583333335),\n (49.09348958333334, 49.25348958333334),\n (50.603489583333335, 53.463489583333335),\n (54.54348958333334, 54.58348958333334),\n (55.72348958333334, 57.61348958333334),\n (60.23348958333334, 61.77348958333334),\n (63.813489583333336, 65.68348958333333),\n (66.90348958333333, 72.19348958333333),\n (75.39348958333333, 77.98348958333334),\n (79.40348958333333, 82.43348958333333),\n (83.63348958333333, 83.99348958333333),\n (85.31348958333334, 94.54348958333333),\n (96.37348958333334, 97.50348958333333),\n (102.74348958333333, 110.03348958333333),\n (111.15348958333333, 111.41348958333333),\n (113.48348958333334, 115.37348958333334),\n (118.58348958333333, 119.22348958333333),\n (122.69348958333333, 122.71348958333333),\n (127.09348958333334, 127.30348958333333)]"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Generation of the time intervals where there is a significant participation of the adult (>= 1 second)\n",
    "threshold_time_interval = 1\n",
    "tuples_pitch_times_adult = []\n",
    "tuples_pitch_indexes_adult = []\n",
    "prev_sec = secs_pitch_adult[0]\n",
    "prev_index = 0\n",
    "curr_time_tuple = (secs_pitch_adult[0],)\n",
    "curr_index_tuple = (0,)\n",
    "for i in range(1,len(secs_pitch_adult)):\n",
    "    next_sec = secs_pitch_adult[i]\n",
    "    next_index = i\n",
    "    time_diff = next_sec - prev_sec\n",
    "    if(time_diff>threshold_time_interval):\n",
    "        curr_time_tuple+=(prev_sec,)\n",
    "        curr_index_tuple+=(prev_index,)\n",
    "        tuples_pitch_times_adult.append(curr_time_tuple)\n",
    "        tuples_pitch_indexes_adult.append(curr_index_tuple)\n",
    "        curr_time_tuple = (next_sec,)\n",
    "        curr_index_tuple = (next_index,)\n",
    "    prev_sec = next_sec\n",
    "    prev_index = next_index\n",
    "tuples_pitch_times_adult"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "[(2.4734895833333344, 3.193489583333334),\n (45.07348958333334, 45.07348958333334),\n (47.12348958333334, 48.033489583333335),\n (49.09348958333334, 49.25348958333334),\n (54.54348958333334, 54.58348958333334),\n (96.37348958333334, 97.50348958333333),\n (111.15348958333333, 111.41348958333333),\n (118.58348958333333, 119.22348958333333),\n (122.69348958333333, 122.71348958333333),\n (127.09348958333334, 127.30348958333333)]"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Potential false positives (child segments that are detected as adult)\n",
    "tuples_pitch_times_adult_but_child = []\n",
    "\n",
    "#Indexes that should be removed\n",
    "indexes_to_remove = []\n",
    "\n",
    "#checks avg pitch for each segment\n",
    "for i in range(0,len(tuples_pitch_indexes_adult)):\n",
    "    curr_index_tuple = tuples_pitch_indexes_adult[i]\n",
    "    start_index = curr_index_tuple[0]\n",
    "    end_index = curr_index_tuple[1]\n",
    "    sum = 0\n",
    "    for j in range(start_index,end_index+1):\n",
    "        sum = sum + pitch_values_adult[j]\n",
    "    n_frames = end_index-start_index\n",
    "    avg=sum/n_frames\n",
    "    if(avg>=240):\n",
    "        tuples_pitch_times_adult_but_child.append(tuples_pitch_times_adult[i])\n",
    "        indexes_to_remove.append(i)\n",
    "tuples_pitch_times_adult_but_child"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.collections.PolyCollection at 0x7fa9e952b2e0>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 1280x960 with 1 Axes>",
      "image/png": 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v3r1z0EEH5ec//3nDanryySfzz3/+s8PrTZgwITfddFOn5pz7RN6dNWtW178WBgAAAFCqW49ImmODDTbIMcccs8D9TU1N+fKXv5z//u//zr///e/MmDEj73rXu7LCCis0tJ6rrrqqdvuII47I4MGD213+8ccfz4UXXphk9km35xwptfrqq9eWefPNN7Pxxhu3OcacI65aM/e5ldr7zvvkyZPbrRMAAACgnnokSFqYvn375t3vfne3zDVjxoxcf/31SZJll102Rx111EKDq5133jmXXXZZJk+enL///e958skn8+53v3ue4OiRRx7Jdttt1+YYjz/+eJuP9e79/34t06dPb3O5V199td06AQAAAOqp27/a1pZ33nknM2fO7PZ5b7/99kyYMCHJ7PM0lRz9tOyyy+YTn/hE7eeRI0cmSXbaaaf069cvSXLttdfOc6Lwub3zzjvtfiWuf//+tdsvvvhiq8tMmzYt999//0JrbU2vXovMrx0AAABYjPRYojBmzJj8z//8Tz7+8Y9n8ODB2WKLLfLb3/629vjw4cNz7rnn5q233mpoHXOfZHufffYpXm///fev3b7++uszZcqULLPMMvnMZz6TJPn3v/+d733vewusV61Wc9ppp2XcuHFtjr3ZZpvVbl966aVpaZn3qmazZs3KmWeeWQvAOqpv376121OnTu3UGAAAAMDSp9u/2jZu3LiccMIJGTNmTO2+arU6z3mBkuTBBx/MnXfemZEjR+Z73/tedtttt7rX8tprr+Vvf/tbkmTAgAHZcccdi9cdPHhwNtlkkzz99NOZMmVKrr/++nzqU5/KMccck9tvvz3PPvtsfve73+Xpp5/OZz7zmay99tp58cUX87vf/S4PPPBAll9++TZDnJ133jkrr7xyJkyYkNGjR+eII47IIYccktVWWy1jx47N5Zdfnocffjjrr79+/vOf/3T4ea+88srp06dPZs6cmRtuuCE77LBD+vfvn3XXXTcDBgzo8HgAAADA0qFbj0h67bXXcsABB2TMmDGpVqu1/+Y3adKk2omk33777Rx33HH585//XPd6rr322trRPnvsscc85yYq8clPfrJ2+/LLL0+SLLPMMvntb3+bLbbYIsnsI6+++tWv5oADDshxxx2XBx54IOutt16OP/74NsddYYUVcvbZZ2eZZZZJktx777358pe/nIMOOignnXRSHn744QwZMiTf/e53O1TvHL17986uu+6aJHn99ddz5JFH5sADD8ytt97aqfEAAACApUO3BknHHntsXn311VSr1WyyySb5wQ9+0Gp4seKKK2bEiBHZZJNNkiQtLS055ZRTOv1VrrZce+21tdt77713h9ffZ5990qdPnyTJE088kUceeSTJ7KObfve73+WHP/xhtttuuwwcODDLLLNMNtxwwwwfPjzXXnttVltttXbH3mWXXXLjjTfmkEMOyfrrr5++fftm5ZVXzrbbbpvvfe97+b//+78st9xyHa55ju9973v5zGc+kzXWWCN9+vTJgAED6r59AQAAgCVLpdre9eXr6Oabb85XvvKVVCqV7LbbbjnvvPPS1NSUJHn3u9+dSqWSE088MZ/73Odq68ycOTMnnHBCbr755lQqlRx//PE58sgju6Ncusn48VPT3Nyy8AVhIQYM6Jempl5paZmVt96a0tPlsATQU9SbnqLe9BSNoK+oNz3Vc3r3bsoqqyxf93G77YikG2+8McnsK5KdeeaZtRCpPX369MmZZ56ZlVZaKUly5513NrRGAAAAANrWbUHSo48+mkqlkl133TUrrLBC8XorrLBChg4dmmq1mmeeeaaBFQIAAADQnm4Lkt58880kyfrrr9/hddddd90kqZ2AGwAAAIDu121B0rLLLpskmTFjRofXnTRpUpKkX79+da0JAAAAgHLdFiStueaaSVK7sllH3H333UmStdZaq641AQAAAFCu24KkHXbYIdVqNffee2+efPLJ4vWuvPLKPP3006lUKtluu+0aWCEAAAAA7em2IOmAAw5IU1NTqtVqjjnmmLzwwgsLXeeKK67I6aefniSpVCrZb7/9Gl0mAAAAAG3o3V0TbbTRRjnssMNy8cUX58UXX8xee+2VPffcM+95z3tqy7z++uu555578uijj+aPf/xjnnnmmVSr1VqItOmmm3ZXuQAAAADMp1KtVqvdNVm1Ws3Xvva13HTTTbMnr1QWunySDBkyJBdddFH69OnT8BrpXuPHT01zc0tPl8ESYMCAfmlq6pWWlll5660pPV0OSwA9Rb3pKepNT9EI+op601M9p3fvpqyyyvJ1H7fbvtqWzA6OfvSjH+Wb3/xmVllllVSr1dp/Seb5uVqtZrnllssXv/jF/O///q8QCQAAAKCHddtX2+Z22GGH5aCDDsott9ySMWPG5Nlnn83EiRPT3NyclVZaKeuss0622WabfPzjH8/KK6/cEyUCAAAAMJ9u/WobzK8zX23r27d3+vXru9CvRi5MtVrNlCkzMmNGc/Ec7a3T3rqdmWtRVbIN5ujotmhrnRK9elVSqVTaPGR2/nFLn0dXfj8d2Vb1mrOr9bQ3d0f6uJHPvaNjd7WnqtVqJk2a3qHttiS95uupnq//zvRYT2/7uXtq1qy2d786+/qZo7Ov49IxSjTqvb6eNXTFwupvxNytzbmwnmrE77ur+wH1GrsRSuvt6udp6Rgdrauj47ZlzteQFvZe1Yi5O6rR71ULm7P0vS5Jw97XFwdtvVfV47VUD13db0269vvt6Hwd3RZNTfX/IlqPHJEEXdGvX9/07t1Ut7Fae8G3N0db6yxs3c7Mtaha2DaYe7mObIv21inVq1frb6ytjVvyPLpaT+m2quecXalnYXN3pI8b+dw7MnZXt2elUunUdluSXvP1VM/Xf0d7bFHZ9pVKJU1N7e8Edub1M/e6nXkdd2SM0joa9V5fjxq6Ou7C6q/33O3N2V5PNeL33dX9gHqM3Qgdqbern6clY3Smro6M25Y5+1Il71X1nrujGv1eVTJn6XtdI9/XFxet9VQ9Xkv10NX91u7o/UWpD3o0SJoxY0YefPDBvPzyy3nzzTfTp0+fDBw4MOutt14GDx7ck6WxCKslsLNakrdf7dwgK6yZ9GpqM81tdY6FrNPmup2Za1FVuA3m6Oi2aHWdDtZWNG5S/Dy6Wk9n/nrSkJ7obP8Wrt/Z7Vs8f2EdnRqzPZ3ZbsmS85qvp3q+/jv5+lostn0X3jvm6OzruGiMEo18r69jDV3Rbv0NmrvD26wRv++u7gfUqd5GKaq3q5+nHRijQ3V1YtyF6sjrs4d+f93xGd/mnG383NZjDXlfX5zV47XUjXW0pl6/3w7P15Ft0dQ36Tew7rX0SJD07LPP5oILLshdd92VadOmtbrMaqutlt133z1HHXWU8yTRurdfTc57T+fW/drjSf+1OzZH6Trzr9uZuRZVHd0Gc3R0W8y9Tr1rm/Om29Hn0ah66jlnPeuZf+5Gb9+Fzd/ROjoyZns6s92SJec1X0/1fP139fW1KG/7erx3zNHZ13F7Y5Ro5Ht9I2roitbqb/TcpdusEb/vru4HtKe7fmcl2qu3q5+nnRmjpK6ujNvZ+Ro5d0d1x2f8omBR/vzqqHq8lnqijkVBR7bFekOSz99c9xK69aptSTJixIjss88+ufnmmzN16tQFrtQ257833ngjl156aXbffffccsst3V0mAAAAAPPp1iOSfvnLX2bEiBG1E2317t07W2yxRTbeeOOstNJKaWlpycSJE/Ovf/0rjz32WFpaWjJ+/Pgcd9xx+dWvfpUhQ4Z0Z7kAAAAAzKXbgqQnn3wyP/7xj5PMPiv6IYcckqOOOioDBgxodfnXX389F1xwQa688so0NzfnK1/5Sv785z9npZVW6q6SAQAAAJhLt3217be//W1mzZqVSqWSr3/96/nWt77VZoiUJKuvvnrOOOOMHH300UmSSZMm5bLLLuuucgEAAACYT7cFSffdd18qlUoGDRqUI444oni9o446Ku9617uSxLmSAAAAAHpQtwVJr746+0o2H/7whzu0Xq9evbLLLrukWq1m7NixjSgNAAAAgALdFiQtv/zySZI+ffp0eN0VV1wxyexQCQAAAICe0W3JzEYbbZQkefDBBzu87lNPPZUk2WCDDepZEgAAAAAd0G1B0ic/+clUq9WMHj06d9xxR/F6//73v3PrrbemUqlkn332aWCFAAAAALSn24Kk/fffPzvttFOq1Wq+9rWv5cYbb1zoOs8++2yGDx+emTNnZrPNNstnPvOZbqgUAAAAgNb07q6JXn755Zx88sl55513MmbMmBx//PH5v//7v3ziE5/I+973vgwYMCB9+vTJ5MmT8+yzz+auu+7KzTffnBkzZqRPnz7ZY489csMNN7Q7x7Bhw7rnyQAAAAAshbotSNp1111TqVSSJJVKJdVqNf/4xz/yj3/8o811qtVqKpVKmpub88Mf/rDd8SuViiAJAAAAoIG6LUhKZgdD7f1csg4AAAAAPaPbgqSjjz66u6YCAAAAoAEESQAAAAAU6bartgEAAACweOvWcyS1p7m5Offee2+ee+65zJw5M5tsskm233779O69yJQIAAAAsFRreErzl7/8JXfccUeq1WpOP/30VpcZNWpUfvzjH+e1116b5/5VV1013/jGN7LXXns1ukwAAAAAFqJhQdJbb72Vo446Ko888kiS2aFQa0HSxRdfnO9///utXp3tjTfeyIknnpgXXnghRx11VKNKBQAAAKBAQ4KkN998M4ccckiee+65JEm1Ws3EiRMXWO7xxx/PD3/4wyRJpVJJtVrN9ttvn0GDBuU///lP7rzzzsyaNSsXXHBBNt1003zkIx9pRLkAAAAAFGhIkHTuuedm7NixqVQqWWaZZTJs2LDsuOOOCyz3ox/9KC0tLUmSXr165Qc/+EH23HPP2uOPPvpojjzyyEyaNCnf+9738qEPfSh9+/ZtRMkAAAAALETdr9r23HPPZdSoUal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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#https://www.geeksforgeeks.org/python-basic-gantt-chart-using-matplotlib/\n",
    "# Declaring a figure \"gnt\"\n",
    "fig, gnt = plt.subplots()\n",
    "\n",
    "# Setting Y-axis limits\n",
    "gnt.set_ylim(0, 30)\n",
    "\n",
    "# Setting X-axis limits\n",
    "gnt.set_xlim(0, snd.duration)\n",
    "\n",
    "# Setting labels for x-axis and y-axis\n",
    "gnt.set_xlabel('Time [s]')\n",
    "gnt.set_ylabel('Speaker')\n",
    "\n",
    "# Setting ticks on y-axis\n",
    "gnt.set_yticks([5,15])\n",
    "# Labelling tickes of y-axis\n",
    "gnt.set_yticklabels(['Child',\"Adult\"])\n",
    "\n",
    "# Setting graph attribute\n",
    "gnt.grid(True)\n",
    "\n",
    "#get data in the format that the plotter requires (second_start, duration_span)\n",
    "timespan_data_child = []\n",
    "for i in range(0,len(tuples_pitch_times_child)):\n",
    "    time_tuple = tuples_pitch_times_child[i]\n",
    "    plot_format_tuple = (time_tuple[0],time_tuple[1]-time_tuple[0])\n",
    "    timespan_data_child.append(plot_format_tuple)\n",
    "\n",
    "timespan_data_adult = []\n",
    "for i in range(0,len(tuples_pitch_times_adult)):\n",
    "    time_tuple = tuples_pitch_times_adult[i]\n",
    "    plot_format_tuple = (time_tuple[0],time_tuple[1]-time_tuple[0])\n",
    "    timespan_data_adult.append(plot_format_tuple)\n",
    "\n",
    "# Declaring multiple bars in at same level and same width\n",
    "gnt.broken_barh(timespan_data_child, (5, 9),\n",
    "                         facecolors ='tab:orange')\n",
    "gnt.broken_barh(timespan_data_adult, (15, 9),\n",
    "                         facecolors ='tab:blue')"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Load audio for slicing purposes\n",
    "audio = AudioSegment.from_wav(filename)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Play adult segments\n",
    "#play_audio_segment(audio,274760,277030)\n",
    "#play_audio_segment(audio,99690, 100980)\n",
    "#play_audio_segment(audio,17430,18530)\n",
    "#play_audio_segment(audio,274760,277730)\n",
    "\n",
    "#dad-child audios\n",
    "play_audio_segment(audio,85242,88042)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Play child segments\n",
    "#play_audio_segment(audio,98860,100200)\n",
    "#play_audio_segment(audio,99700,100980)#wrongly labeled as adult\n",
    "#play_audio_segment(audio,295110,295600)#wrongly labeled as adult\n",
    "#play_audio_segment(audio,188960,189600)#wrongly labeled as adult\n",
    "#play_audio_segment(audio,88330,89110)#wrongly labeled as adult\n",
    "#play_audio_segment(audio,294420,296090)#wrongly labeled as adult\n",
    "\n",
    "#dad-child audios\n",
    "play_audio_segment(audio,137822,139842)\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Play all the child segments\n",
    "print(len(tuples_pitch_times_child))\n",
    "for i in range(5,10):#\n",
    "    time_tuple = tuples_pitch_times_child[i]\n",
    "    print(time_tuple)\n",
    "    play_audio_segment(audio,round(time_tuple[0]*1000),round(time_tuple[1]*1000))\n",
    "    time.sleep(1)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Play all the adult segments\n",
    "for i in range(15,20):#len(tuples_pitch_times_adult)):\n",
    "    time_tuple = tuples_pitch_times_adult[i]\n",
    "    print(time_tuple)\n",
    "    play_audio_segment(audio,time_tuple[0]*1000,time_tuple[1]*1000)\n",
    "    time.sleep(1)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Play all the adult segments that should be child\n",
    "for i in range(0,1):#len(tuples_pitch_times_adult_but_child)):\n",
    "    time_tuple = tuples_pitch_times_adult_but_child[i]\n",
    "    print(time_tuple)\n",
    "    play_audio_segment(audio,round(time_tuple[0]*1000),round(time_tuple[1]*1000))\n",
    "    time.sleep(1)"
   ],
   "metadata": {
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    "pycharm": {
     "is_executing": true
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Segment the audio in smaller chunks\n",
    "from pydub.utils import make_chunks\n",
    "\n",
    "audio_to_chunk = AudioSegment.from_file(filename , \"wav\")\n",
    "chunk_length_ms = 2000 # pydub calculates in millisec\n",
    "chunks = make_chunks(audio_to_chunk, chunk_length_ms) #Make chunks of one sec\n",
    "\n",
    "#Export all of the individual chunks as wav files\n",
    "for i, chunk in enumerate(chunks):\n",
    "    chunk_name = \"../EMBRACE-data-analysis/audios/asu/mom-child-{0}.wav\".format(i)\n",
    "    print(\"exporting\", chunk_name)\n",
    "    chunk.export(chunk_name, format=\"wav\")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Speaker diarization with pyannote\n",
    "pipeline_diarization = Pipeline.from_pretrained(\"pyannote/speaker-diarization@2.1\",\n",
    "                                    use_auth_token=\"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\")\n",
    "\n",
    "# apply the pipeline to an audio file\n",
    "diarization = pipeline_diarization(filename)\n",
    "\n",
    "# dump the diarization output to disk using RTTM format\n",
    "with open(\"diarization.rttm\", \"w\") as rttm:\n",
    "    diarization.write_rttm(rttm)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Overlap detection with pyannote\n",
    "pipeline_overlap = Pipeline.from_pretrained(\"pyannote/overlapped-speech-detection\",\n",
    "                                    use_auth_token=\"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\")\n",
    "\n",
    "#filename_overlap = \"../EMBRACE-data-analysis/dad-child-14.wav\"\n",
    "#filename_overlap = \"../EMBRACE-data-analysis/mom-grandmom-child-28.wav\"\n",
    "filename_overlap = \"../EMBRACE-data-analysis/mom-child-20.wav\"\n",
    "\n",
    "output = pipeline_overlap(filename_overlap)\n",
    "\n",
    "audio = AudioSegment.from_wav(filename_overlap)\n",
    "\n",
    "#mom-grandmom-child: 9\n",
    "for speech in output.get_timeline().support():\n",
    "    # two or more speakers are active between speech.start and speech.end\n",
    "    print(speech)\n",
    "    play_audio_segment(audio,speech.start*1000,speech.end*1000)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#inter agreement analysis\n",
    "from sklearn.metrics import cohen_kappa_score\n",
    "\n",
    "#read first two files\n",
    "f_coder1 = open(\"../EMBRACE-data-analysis/audios/asu/PAR001_Record-656468528.8997459_silence_removed-Coded.txt\", \"r\")\n",
    "f_coder2 = open(\"../EMBRACE-data-analysis/audios/asu/par001-record-656468528.8997459.wav_labeled_Jordan.txt\", \"r\")\n",
    "\n",
    "coder1_raw_list = f_coder1.readlines()\n",
    "coder2_raw_list = f_coder2.readlines()\n",
    "\n",
    "#code lists\n",
    "coder1_list = []\n",
    "coder2_list = []\n",
    "\n",
    "for line in coder1_raw_list:\n",
    "    code = line.split('\\t')[-1]\n",
    "    coder1_list.append(code[:-1])\n",
    "\n",
    "for line in coder2_raw_list:\n",
    "    code = line.split(' ')[-1]\n",
    "    coder2_list.append(code[:-1])\n",
    "\n",
    "print(len(coder1_list))\n",
    "print(len(coder2_list))\n",
    "\n",
    "cohen_kappa_score(coder1_list, coder2_list)"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "#Audio ASU mom-child\n",
    "filename1 = '../EMBRACE-data-analysis/data/asu/par007_record-673758082.558921.wav'\n",
    "\n",
    "#Audio dad-child (Pittsburgh)\n",
    "#filename='../EMBRACE-data-analysis/audios/record-667269360.9571331.wav'\n",
    "#filename='../EMBRACE-data-analysis/audios/record-667269360.9571331_reduced_noise.wav'\n",
    "\n",
    "#ASU par001\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par001-record-656468528.8997459_silence_removed.wav'\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par001-record-656468528.8997459.wav'\n",
    "\n",
    "#ASU par010 (with Sindhu there)\n",
    "#filename = '../EMBRACE-data-analysis/audios/asu/par010-record-691979477.209939.wav'\n",
    "\n",
    "#ASU par102\n",
    "filename2 = \"../EMBRACE-data-analysis/data/asu/par102-record-666060012.245397.wav\"\n",
    "\n",
    "#ASU par003\n",
    "filename3 = \"../EMBRACE-data-analysis/data/asu/par003-record-674009351.193422.wav\"\n",
    "\n",
    "#ASU par001\n",
    "filename4 = '../EMBRACE-data-analysis/data/asu/par001-record-656468528.8997459.wav'\n",
    "\n",
    "filenames = [filename1,filename2,filename3,filename4]\n",
    "sound_objects = []\n",
    "segments_data = []\n",
    "#Get active voice segments\n",
    "active_voice_segments = []\n",
    "segment_index = 0\n",
    "for i in range(0,len(filenames)):#len(filenames)):\n",
    "    active_voice_segments.append(get_voice_activity(filenames[i],True,False,True))\n",
    "    segments_voice_activity = custom_size_segments(active_voice_segments[i])\n",
    "\n",
    "    #Load audio\n",
    "    sound_objects.append(parselmouth.Sound(filenames[i]))\n",
    "\n",
    "    #Get pitch values\n",
    "    curr_pitch = sound_objects[i].to_pitch()\n",
    "\n",
    "    #Get mfcc coefs\n",
    "    curr_mfcc_coefs = sound_objects[i].to_mfcc()\n",
    "\n",
    "    pitch_values = curr_pitch.selected_array['frequency']\n",
    "\n",
    "\n",
    "    for j in range(0,len(segments_voice_activity)):\n",
    "        print(segments_voice_activity[j])\n",
    "        segments_data.append([])\n",
    "        active_segment = segments_voice_activity[j]\n",
    "        #print(active_segment)\n",
    "        #predicted_label_str = classify_audio_freq(avg_pitch(pitch,70,400,[active_segment]))\n",
    "        pitch_values_active_segment = extract_pitch_values_segment(curr_pitch,active_segment)\n",
    "        segments_data[segment_index].append(pitch_values_active_segment)\n",
    "        segment_index = segment_index + 1\n",
    "        print(len(pitch_values_active_segment))\n",
    "\n",
    "    #print(len(curr_pitch))\n",
    "    #print(len(curr_mfcc_coefs))\n",
    "    #numeric_data_audios[i].append(curr_pitch)\n",
    "    #numeric_data_audios[i].append(curr_mfcc_coefs)\n",
    "\n",
    "    #print(len(numeric_data_audios[i]))\n",
    "\n"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
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   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
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