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from faster_whisper import WhisperModel |
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import os |
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model = None |
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def get_model(): |
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global model |
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if model is None: |
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model = WhisperModel("base", device="cpu", compute_type="int8") |
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return model |
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def transcribe_audio(audio_path: str) -> str: |
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"""Transkribera ljudfil till text""" |
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try: |
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if not os.path.exists(audio_path): |
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return f"Audio file not found: {audio_path}" |
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model = get_model() |
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segments, info = model.transcribe(audio_path, beam_size=5) |
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transcription = " ".join(segment.text for segment in segments) |
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return transcription.strip() or "No transcription found." |
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except Exception as e: |
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return f"Error transcribing audio: {str(e)}" |
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