forked from mrq/ai-voice-cloning
I forget
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@ -1487,6 +1487,11 @@ def prepare_dataset( voice, use_segments=False, text_length=0, audio_length=0, p
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lines = { 'training': [], 'validation': [] }
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segments = {}
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# I'm not sure how the VALL-E implementation decides what's validation and what's not
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if args.tts_backend == "vall-e":
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text_length = 0
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audio_length = 0
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for filename in enumerate_progress(results, desc="Parsing results", progress=progress):
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use_segment = use_segments
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@ -1647,7 +1652,7 @@ def prepare_dataset( voice, use_segments=False, text_length=0, audio_length=0, p
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quantized = valle_quantize( waveform, sample_rate ).cpu()
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torch.save(quantized, qnt_file)
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print("Quantized:", file)
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print("Quantized:", qnt_file)
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for i in enumerate_progress(range(len(jobs['phonemize'][0])), desc="Phonemizing", progress=progress):
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phn_file = jobs['phonemize'][0][i]
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@ -1655,7 +1660,7 @@ def prepare_dataset( voice, use_segments=False, text_length=0, audio_length=0, p
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phonemized = valle_phonemize( normalized )
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open(phn_file, 'w', encoding='utf-8').write(" ".join(phonemized))
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print("Phonemized:", file)
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print("Phonemized:", phn_file)
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training_joined = "\n".join(lines['training'])
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validation_joined = "\n".join(lines['validation'])
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