forked from mrq/ai-voice-cloning
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@ -496,7 +496,7 @@ def prepare_dataset( files, outdir ):
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torchaudio.save(f"{outdir}/{sliced_name}", sliced_waveform, sampling_rate)
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torchaudio.save(f"{outdir}/{sliced_name}", sliced_waveform, sampling_rate)
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transcription.append(f"{sliced_name}|{segment['text'].trim()}")
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transcription.append(f"{sliced_name}|{segment['text'].strip()}")
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idx = idx + 1
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idx = idx + 1
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with open(f'{outdir}/whisper.json', 'w', encoding="utf-8") as f:
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with open(f'{outdir}/whisper.json', 'w', encoding="utf-8") as f:
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@ -428,7 +428,7 @@ def setup_gradio():
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gr.Checkbox(label="Use CUDA for Voice Fixer", value=args.voice_fixer_use_cuda),
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gr.Checkbox(label="Use CUDA for Voice Fixer", value=args.voice_fixer_use_cuda),
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gr.Checkbox(label="Force CPU for Conditioning Latents", value=args.force_cpu_for_conditioning_latents),
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gr.Checkbox(label="Force CPU for Conditioning Latents", value=args.force_cpu_for_conditioning_latents),
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gr.Textbox(label="Device Override", value=args.device_override),
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gr.Textbox(label="Device Override", value=args.device_override),
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gr.Dropdown(label="Whisper Model", value=args.whisper_model, choices=["tiny", "base", "small", "medium", "large"]),
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gr.Dropdown(label="Whisper Model", value=args.whisper_model, choices=["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large"]),
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]
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]
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gr.Button(value="Check for Updates").click(check_for_updates)
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gr.Button(value="Check for Updates").click(check_for_updates)
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gr.Button(value="Reload TTS").click(reload_tts)
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gr.Button(value="Reload TTS").click(reload_tts)
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