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| import os | |
| from pydub import AudioSegment | |
| import whisper | |
| from deep_translator import GoogleTranslator | |
| # @title Audio into chunks | |
| def audio_into_chunks_transcribe_translate(audio_file,lang): | |
| chunk_length_seconds=11 | |
| output_format="wav" | |
| # Check if file exists | |
| if not os.path.exists(audio_file): | |
| raise ValueError(f"FLAC file not found: {audio_file}") | |
| Transcribe_Text=[] | |
| # Load the FLAC audio | |
| audio_segment = AudioSegment.from_file(audio_file, format="flac") | |
| #load Model For Transcribe | |
| model = whisper.load_model("medium") | |
| # Get total audio duration in milliseconds | |
| total_duration_ms = audio_segment.duration_seconds * 1000 | |
| # Calculate chunk duration in milliseconds | |
| chunk_duration_ms = chunk_length_seconds * 1000 | |
| # Split audio into chunks | |
| start_time = 0 | |
| chunk_num = 1 | |
| while start_time < total_duration_ms: | |
| # Get the end time for the current chunk | |
| end_time = min(start_time + chunk_duration_ms, total_duration_ms) | |
| # Extract the current chunk | |
| chunk = audio_segment[start_time:end_time] | |
| # Generate output filename with sequential numbering | |
| output_filename = f"{os.path.splitext(os.path.basename(audio_file))[0]}_chunk_{chunk_num}.{output_format}" | |
| # Export the chunk as the specified format | |
| chunk.export(output_filename, format=output_format) | |
| # Update start time for the next chunk | |
| start_time += chunk_duration_ms | |
| chunk_num += 1 | |
| #transcribe Chunks | |
| result = model.transcribe(output_filename) | |
| #translate the transcribe data | |
| translator=GoogleTranslator(source='auto',target=lang) | |
| data_trans=translator.translate(result['text']) | |
| Transcribe_Text.append(data_trans) | |
| print(data_trans) | |
| print(result['text']) | |
| return Transcribe_Text | |
| print(f"FLAC file '{flac_filepath}' successfully split into {chunk_num - 1} chunks.") | |