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| # presentation/infrastructure/services/audio/transcriber_vosk.py | |
| from vosk import Model, KaldiRecognizer | |
| import wave | |
| import json | |
| import os | |
| from audio_converter import convert_to_pcm16_mono | |
| model = Model("models/vosk-model-small-es-0.42") | |
| def transcribe_audio(file_path: str) -> str: | |
| converted_path = convert_to_pcm16_mono(file_path) | |
| wf = wave.open(converted_path, "rb") | |
| rec = KaldiRecognizer(model, wf.getframerate()) | |
| result_text = [] | |
| while True: | |
| data = wf.readframes(4000) | |
| if len(data) == 0: | |
| break | |
| if rec.AcceptWaveform(data): | |
| res = json.loads(rec.Result()) | |
| result_text.append(res.get("text", "")) | |
| final = json.loads(rec.FinalResult()) | |
| result_text.append(final.get("text", "")) | |
| wf.close() | |
| if converted_path != file_path: | |
| try: | |
| os.remove(converted_path) | |
| except Exception: | |
| pass | |
| return " ".join(result_text) | |