38 lines
959 B
Python
38 lines
959 B
Python
from transcription.audio import Audio
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import torchaudio
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class AudioPreprocessor:
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TARGET_SAMPLING_RATE: int = 16000
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# for different models in future
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# def __init__(self, model):
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# pass
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def __init__(self, target_sr: int) -> None:
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self.TARGET_SAMPLING_RATE = target_sr
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def _resample(
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self,
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audio: Audio
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) -> None:
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if audio.sr != self.TARGET_SAMPLING_RATE:
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audio.waveform = torchaudio.functional.resample(
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audio.waveform,
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audio.sr,
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self.TARGET_SAMPLING_RATE
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)
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def _to_mono(
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self,
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audio: Audio
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) -> None:
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if audio.waveform.shape[0] > 1:
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audio.waveform = audio.waveform.mean(dim=0, keepdim=True)
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audio.waveform = audio.waveform.squeeze(0)
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def prepare(
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self,
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audio: Audio
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):
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self._resample(audio)
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self._to_mono(audio) |