Delete code_to_download_datasets_in_wav_or_mp3.ipynb

code_to_download_datasets_in_wav_or_mp3.ipynb

@@ -1,34 +0,0 @@
-from datasets import load_dataset
-import soundfile as sf, os, pandas as pd, re
-from tqdm import tqdm
-
-dataset = load_dataset("mozilla-foundation/common_voice_17_0", "ja", split="other", trust_remote_code=True, streaming=True, token="your_token")
-
-name = "other"
-ouput_dir = "./datasets/CV17/"
-output_file = 'metadata.csv'
-os.makedirs(ouput_dir + name, exist_ok=True)
-folder_path = ouput_dir + name # Create a folder to store the audio and transcription files
-
-char = '[　０１２３４５６７８９ａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖｗｘｙｚＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890]'
-special_characters = '[♬「」？！“%‘”~♪…?!゛＃＄％＆（）＊＋：；〈＝〉＠＾＿｛｜｝～"█♩♫』『.;:<>_()*&^$#@`, ]'
-
-dsa = (dataset
-       .filter(lambda sample: bool(sample["sentence"]))
-       .filter(lambda sample: not re.search(char, sample["sentence"]))
-       .filter(lambda sample: sample["down_votes"] == 0)
-       )
-
-for i, sample in tqdm(enumerate(dsa)): # Process each sample in the filtered dataset
-    audio_sample = name + f'_{i}.wav' # or wav
-    audio_path = os.path.join(folder_path, audio_sample)
-    transcription_path = os.path.join(folder_path, output_file)  # Path to save transcription file 
-    if not os.path.exists(audio_path):
-        sf.write(audio_path, sample['audio']['array'], sample['audio']['sampling_rate'])
-        sample["audio_length"] = len(sample["audio"]["array"]) / sample["audio"]["sampling_rate"]  # Get audio length, remove if not needed
-        with open(transcription_path, 'a', encoding='utf-8') as transcription_file: # Save transcription file    
-            transcription_file.write(audio_sample+",") # Save transcription file name  
-            sample["sentence"] = re.sub(special_characters,'', sample["sentence"])
-            transcription_file.write(sample['sentence']) # Save transcription 
-            transcription_file.write(str(","+str(sample['audio_length']))) # Save audio length, remove if not needed
-            transcription_file.write('\n')