utilities.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def timestamps(total_time, split):\n",
    "    iters = int(total_time/split)\n",
    "    for i in range(1, iters + 1):\n",
    "        yield (i-1)*split, i * split, i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydub import AudioSegment\n",
    "import pathlib\n",
    "import os\n",
    "\n",
    "def split_audio(filename, tag=\"\", split=2500):\n",
    "\n",
    "    pathlib.Path(f'audio/{filename}{tag}').mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "    newAudio = AudioSegment.from_wav(f\"audio/FULL_INTERVIEWS/{filename}.wav\")\n",
    "\n",
    "    for start, end, val in timestamps(len(newAudio), split):\n",
    "        cutAudio = newAudio[start:end]\n",
    "        cutAudio.export(f'audio/{filename}{tag}/{filename}{tag}_{val-1}.wav', format='wav')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import numpy as np\n",
    "import os\n",
    "import librosa\n",
    "\n",
    "header = 'filename chroma_stft rmse spectral_centroid spectral_bandwidth rolloff zero_crossing_rate'\n",
    "for i in range(1, 21):\n",
    "    header += f' mfcc{i}'\n",
    "header += ' label'\n",
    "header = header.split()\n",
    "\n",
    "def create_dataset(foldernames, dataname):\n",
    "    \n",
    "    file = open(f'datasets/{dataname}.csv', 'w', newline='')\n",
    "\n",
    "    with file:\n",
    "        writer = csv.writer(file)\n",
    "        writer.writerow(header)\n",
    "\n",
    "    for p in foldernames:\n",
    "        for filename in os.listdir(f'audio/{p}'):\n",
    "            songname = f'audio/{p}/{filename}'\n",
    "            y, sr = librosa.load(songname, mono=True, duration=5)\n",
    "\n",
    "            rmse = librosa.feature.rms(y=y) #root mean squred ENERGY note. changed to rms form rmse\n",
    "            chroma_stft = librosa.feature.chroma_stft(y=y, sr=sr)\n",
    "            spec_cent = librosa.feature.spectral_centroid(y=y, sr=sr)\n",
    "            spec_bw = librosa.feature.spectral_bandwidth(y=y, sr=sr)\n",
    "            rolloff = librosa.feature.spectral_rolloff(y=y, sr=sr)\n",
    "            zcr = librosa.feature.zero_crossing_rate(y)\n",
    "            mfcc = librosa.feature.mfcc(y=y, sr=sr)\n",
    "\n",
    "            to_append = f'{filename} {np.mean(chroma_stft)} {np.mean(rmse)} {np.mean(spec_cent)} {np.mean(spec_bw)} {np.mean(rolloff)} {np.mean(zcr)}'\n",
    "\n",
    "            for e in mfcc:\n",
    "                to_append += f' {np.mean(e)}'\n",
    "\n",
    "            to_append += f' {p}'\n",
    "\n",
    "            file = open(f'datasets/{dataname}.csv', 'a', newline='')\n",
    "            with file:\n",
    "                writer = csv.writer(file)\n",
    "                writer.writerow(to_append.split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "split_audio('roganclimate', tag='2500')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "create_dataset(foldernames=['roganclimate2500'], dataname='climate2500')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[youtube] eJFfoSQcC0A: Downloading webpage\n",
      "[download] Destination: audio\\test.mp3\n",
      "[download] 100% of 5.06MiB in 00:02                  \n",
      "[ffmpeg] Post-process file audio\\test.mp3 exists, skipping\n"
     ]
    }
   ],
   "source": [
    "import youtube_dl\n",
    "\n",
    "ydl_opts = {\n",
    "    'outtmpl': 'audio/test.mp3',\n",
    "    'format': 'bestaudio/best',\n",
    "    'postprocessors': [{\n",
    "        'key': 'FFmpegExtractAudio',\n",
    "        'preferredcodec': 'mp3',\n",
    "        'preferredquality': '192',\n",
    "    }],\n",
    "    'prefer_ffmpeg': True,\n",
    "\n",
    "}\n",
    "\n",
    "with youtube_dl.YoutubeDL(ydl_opts) as ydl:\n",
    "    ydl.download([r\"https://www.youtube.com/watch?v=eJFfoSQcC0A\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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