| import whisperx | |
| audio_path = "audio_cut/4.wav" | |
| device = "cuda" | |
| batch_size = 4 # reduce if low on GPU mem | |
| compute_type = "float32" # change to "int8" if low on GPU mem (may reduce accuracy) | |
| # 1. Transcribe with original whisper (batched) | |
| model_dir = "figures/" | |
| model = whisperx.load_model("medium", device, compute_type=compute_type, download_root=model_dir,language="vi") | |
| audio = whisperx.load_audio(audio_path) | |
| result = model.transcribe(audio, batch_size=batch_size,chunk_size=10 | |
| ) | |
| print(result) | |
| import json | |
| # with open('data.json', 'w', encoding='utf-8') as json_file: | |
| # json.dump(data, json_file, ensure_ascii=False, indent=4) | |