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So far, I couldn't find the model which attention works in "reduction factor" = 1. If we use the factor > 1, the prediction would seem like below image. It would be a bad news to wavenet performance.
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In the ReadMe, it's mentioned
> Convert the data generated at the last step which has .f32 extension to what could be loaded with numpy. I merge it to the Tacotron feeder here and here with the fo…
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Criar integração com tacotron
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According to Baidu deep voice 2, it is possible to modify the original Tacotron architecture into multi-speaker version. The main architecture modification is:
:
File "tra…
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I am trying to integrate this model to tacotron 1 for TTS but since I do not have corresponding exact audios that are to be generated from the tacotron's output mel spectrogram, how should I go about …
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I was seeing multiple issue as described in the original paper, like wrong pro, repeat word, or unstoppable case, anyone trying any solution to fix this?