mirror of https://github.com/coqui-ai/TTS.git
extracted id to torch code
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@ -68,6 +68,13 @@ def inv_spectrogram(postnet_output, ap, CONFIG):
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return wav
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def id_to_torch(speaker_id):
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if speaker_id is not None:
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speaker_id = np.asarray(speaker_id)
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speaker_id = torch.from_numpy(speaker_id).unsqueeze(0)
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return speaker_id
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def synthesis(model,
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text,
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CONFIG,
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@ -100,9 +107,7 @@ def synthesis(model,
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style_mel = compute_style_mel(style_wav, ap, use_cuda)
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# preprocess the given text
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inputs = text_to_seqvec(text, CONFIG, use_cuda)
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if speaker_id is not None:
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speaker_id = np.asarray(speaker_id)
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speaker_id = torch.from_numpy(speaker_id).unsqueeze(0)
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speaker_id = id_to_torch(speaker_id)
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if use_cuda:
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speaker_id.cuda()
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# synthesize voice
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@ -116,4 +121,4 @@ def synthesis(model,
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# trim silence
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if trim_silence:
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wav = trim_silence(wav)
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return wav, alignment, decoder_output, postnet_output, stop_tokens
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return wav, alignment, decoder_output, postnet_output, stop_tokens
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