forked from mrq/ai-voice-cloning
oops x2
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@ -471,6 +471,7 @@ def prepare_dataset( files, outdir ):
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idx = 0
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results = {}
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transcription = []
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for file in files:
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print(f"Transcribing file: {file}")
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@ -483,7 +484,6 @@ def prepare_dataset( files, outdir ):
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waveform, sampling_rate = torchaudio.load(file)
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num_channels, num_frames = waveform.shape
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transcription = []
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for segment in result['segments']:
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start = int(segment['start'] * sampling_rate)
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end = int(segment['end'] * sampling_rate)
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