Upload code_to_download_datasets_in_wav_or_mp3.ipynb

code_to_download_datasets_in_wav_or_mp3.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "import soundfile as sf, os, pandas as pd, re\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "dataset = load_dataset(\"Sin2pi/JA_audio_JA_text_180k_samples\", trust_remote_code=True, streaming=True, token=\"your_token\")\n",
+    "\n",
+    "name = \"JA_audio_JA_text_180k_samples\"\n",
+    "output_file = 'metadata.csv'\n",
+    "os.makedirs(\"./datasets/\" + name, exist_ok=True)\n",
+    "folder_path = \"./datasets/\" + name # Create a folder to store the audio and transcription files\n",
+    "\n",
+    "char = '[　０１２３４５６７８９ａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖｗｘｙｚＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890]'\n",
+    "special_characters = '[♬「」 ？！;:“%‘” ~♪… ?!゛＃＄％＆（）＊＋：；〈＝〉？＠＾＿‘｛｜｝～\"█♩♫♩ ♩』『.;:<>_()*&^%$#@?!`~, \"]'\n",
+    "dsa = dataset.filter(lambda batch: bool(batch[\"sentence\"])).filter(lambda sample: not re.search(char, sample[\"sentence\"]))\n",
+    "\n",
+    "for i, sample in tqdm(enumerate(dsa)): # Process each sample in the filtered dataset\n",
+    "    audio_sample = name + f'_{i}.mp3' # or wav\n",
+    "    audio_path = os.path.join(folder_path, audio_sample)\n",
+    "    transcription_path = os.path.join(folder_path, output_file)  # Path to save transcription file \n",
+    "    if not os.path.exists(audio_path):\n",
+    "        sf.write(audio_path, sample['audio']['array'], sample['audio']['sampling_rate'])\n",
+    "        sample[\"audio_length\"] = len(sample[\"audio\"][\"array\"]) / sample[\"audio\"][\"sampling_rate\"]  # Get audio length, remove if not needed\n",
+    "        with open(transcription_path, 'a', encoding='utf-8') as transcription_file: # Save transcription file    \n",
+    "            transcription_file.write(audio_sample+\",\") # Save transcription file name  \n",
+    "            sample[\"sentence\"] = re.sub(special_characters,'', sample[\"sentence\"])\n",
+    "            transcription_file.write(sample['sentence']) # Save transcription \n",
+    "            transcription_file.write(str(\",\"+str(sample['audio_length']))) # Save audio length, remove if not needed\n",
+    "            transcription_file.write('\\n') "
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}