38 lines
899 B
Python
38 lines
899 B
Python
import logging
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from faster_whisper import WhisperModel
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def load_model():
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log_level = logging.getLogger().level
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global model
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model = WhisperModel('small', device="cpu", cpu_threads=8, compute_type="int8")
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logging.getLogger().setLevel(log_level)
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def get_model():
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return model
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def faster_whisper_stt(audio_file):
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"""
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Transcribe audio file using whisper-cpp, no additional server/service needed, runs on CPU.
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:param audio_file:
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:param model:
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:return: text
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"""
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if model is None:
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logging.error("Model is not loaded")
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load_model()
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segments, info = model.transcribe(audio_file, beam_size=5)
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print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
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# combines all segments in one string
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text = ''
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for segment in segments:
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text += segment.text + ' '
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return text
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