Generative adversarial network-based postfilter for statistical parametric speech synthesis

@article{Kaneko2017GenerativeAN,
  title={Generative adversarial network-based postfilter for statistical parametric speech synthesis},
  author={Takuhiro Kaneko and Hirokazu Kameoka and Nobukatsu Hojo and Yusuke Ijima and Kaoru Hiramatsu and Kunio Kashino},
  journal={2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2017},
  pages={4910-4914}
}
We propose a postfilter based on a generative adversarial network (GAN) to compensate for the differences between natural speech and speech synthesized by statistical parametric speech synthesis. In particular, we focus on the differences caused by over-smoothing, which makes the sounds muffled. Over-smoothing occurs in the time and frequency directions and is highly correlated in both directions, and conventional methods based on heuristics are too limited to cover all the factors (e.g… CONTINUE READING
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