Speaker Odyssey 2020 Tutorial: Neural statistical parametric speech synthesis
Автор: NII Yamagishi Lab
Загружено: 2020-11-08
Просмотров: 706
Описание:
Presenter: Dr Xin Wang, National Institute of Informatics, Japan
Info: http://www.odyssey2020.org/program_t....
Slides: http://tonywangx.github.io/slide.html
Researchers know how to wire a machine to synthesize intelligible speech from a long time ago, but it is only in the recent years that the researchers find some methods to make the synthetic speech as natural as human speech. In this tutorial, after a general introduction to speech synthesis, we explain those recent methods, particularly the neural-network-based acoustic models (e.g., Tacotron and its variants) and waveform generators (e.g., WaveNet-based ones). We also explain some of the classical methods such as the hidden-Markov-model-based ones, from which we learn the lessons on the artifacts in synthesized speech. Although this tutorial is mainly from the perspective of text-to-speech synthesis, we make an excursion to voice conversion whenever the introduced model is applicable to both tasks.
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