main.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating the NENA Speech Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Repo card metadata block was not found. Setting CardData to empty.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<nena_speech_1_0.NENASpeech at 0x15ae1c0d0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nena_speech_1_0_test import NENASpeech\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download validated examples from Pocketbase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pocketbase import PocketBase\n",
    "\n",
    "def get_examples():\n",
    "    pb = PocketBase('https://pocketbase.nenadb.dev/')\n",
    "\n",
    "    examples = pb.collection(\"examples\").get_full_list(query_params={\n",
    "        \"expand\": \"dialect\",\n",
    "        \"filter\": \"validated=true\",\n",
    "    })\n",
    "\n",
    "    return examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "examples = get_examples()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bucket examples into subsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_examples(examples, test_split=0.10, dev_split=0.10):\n",
    "    subsets = {}\n",
    "\n",
    "    for example in examples:\n",
    "        dialect = example.expand['dialect'].name.lower()\n",
    "        if not subsets.get(dialect):\n",
    "            subsets[dialect] = { 'all': [] }\n",
    "        subsets[dialect]['all'].append(example)\n",
    "\n",
    "    for subset in subsets.values():\n",
    "        for i, example in enumerate(subset['all']):\n",
    "            prog = i / len(subset['all'])\n",
    "\n",
    "            if prog < test_split:\n",
    "                split = 'test'\n",
    "            elif prog < dev_split + test_split:\n",
    "                split = 'dev'\n",
    "            else:\n",
    "                split = 'train'\n",
    "\n",
    "            if not subset.get(split):\n",
    "                subset[split] = []\n",
    "            subset[split].append(example)\n",
    "        \n",
    "        del subset['all']\n",
    "\n",
    "    return subsets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "subsets = split_examples(examples)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create shards"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pydub import AudioSegment\n",
    "import requests\n",
    "import tempfile\n",
    "import tarfile\n",
    "import shutil\n",
    "import os\n",
    "import csv\n",
    "\n",
    "def save_data(subsets):\n",
    "    for dialect, subset in subsets.items():\n",
    "        for split, examples in subset.items():\n",
    "            audio_dir_path = os.path.join(\"audio\", dialect, split)\n",
    "            os.makedirs(audio_dir_path, exist_ok=True)\n",
    "\n",
    "            transcripts = []\n",
    "            transcript_dir_path = os.path.join(\"transcript\", dialect)\n",
    "            os.makedirs(transcript_dir_path, exist_ok=True)\n",
    "            \n",
    "            for example in examples:\n",
    "                pb = PocketBase('https://pocketbase.nenadb.dev/')\n",
    "                audio_url = pb.get_file_url(example, example.speech, {})\n",
    "                response = requests.get(audio_url)\n",
    "                with tempfile.NamedTemporaryFile() as f:\n",
    "                    f.write(response.content)\n",
    "                    f.flush()\n",
    "                    audio = AudioSegment.from_file(f.name)\n",
    "                audio = audio.set_frame_rate(48000)\n",
    "                audio_file_name = f\"nena_speech_{example.id}.mp3\"\n",
    "                audio_file_path = os.path.join(audio_dir_path, audio_file_name)\n",
    "                audio.export(audio_file_path, format=\"mp3\")\n",
    "                \n",
    "                transcripts.append({\n",
    "                    'age': example.age,\n",
    "                    'transcription': example.transcription,\n",
    "                    'translation': example.translation,\n",
    "                    'path': audio_file_name,\n",
    "                })\n",
    "\n",
    "            audio_tar_path = f\"{audio_dir_path}.tar\"\n",
    "            with tarfile.open(audio_tar_path, 'w') as tar:\n",
    "                tar.add(audio_dir_path, arcname=os.path.basename(audio_dir_path))\n",
    "\n",
    "            with open(os.path.join(transcript_dir_path, f\"{split}.tsv\"), 'w', newline='') as f:\n",
    "                writer = csv.DictWriter(f, fieldnames=transcripts[0].keys(), delimiter='\\t')\n",
    "                writer.writeheader()\n",
    "                writer.writerows(transcripts)\n",
    "\n",
    "            shutil.rmtree(audio_dir_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_data(subsets)"
   ]
  }
 ],
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