| |
| import stable_whisper |
| import whisper |
| import json |
|
|
| audio_path = "master.mp3" |
| transcript_path = "transcript.txt" |
| output_path = "aligned_transcription.json" |
|
|
| print("Loading 'medium' model via stable-whisper on GPU...") |
| model = stable_whisper.load_model('medium', device='cuda') |
|
|
| print(f"Loading transcript from: {transcript_path}") |
| with open(transcript_path, "r", encoding="utf-8") as f: |
| transcript_text = f.read() |
|
|
|
|
| print(f"Pre-loading audio from: {audio_path}") |
| audio_data = whisper.load_audio(audio_path) |
|
|
| print("Aligning audio and text on GPU with stable-whisper...") |
| result = model.align(audio_data, transcript_text, language='as') |
|
|
| print(f"Alignment complete. Saving results to {output_path}") |
| result_dict = result.to_dict() |
| with open(output_path, "w", encoding="utf-8") as f: |
| json.dump(result_dict, f, ensure_ascii=False, indent=2) |
|
|
| print("Process finished. You can download the JSON file from the sidebar.") |
