Publications
Preprints
- Takaaki Saeki, Shinnosuke Takamichi, and Hiroshi Saruwatari
Incremental text-to-speech synthesis using pseudo lookahead with large pretrained language model
arXiv:2012.12612 [cs.SD]
[arXiv] [demo]
International conferences (peer-reviewed)
- Takaaki Saeki, Yuki Saito, Shinnosuke Takamichi, and Hiroshi Saruwatari
Real-time, full-band, online DNN-based voice conversion system using a single CPU
Conference of the International Speech Communication Association (INTERSPEECH), 2020. (Show & Tell)
[ISCA Archive] [video] - Naoki Kimura, Zixiong Su, and Takaaki Saeki
End-to-end deep learning speech recognition model for Silent Speech Challenge
Conference of the International Speech Communication Association (INTERSPEECH), 2020. (Show & Tell)
[ISCA Archive] [video] - Takaaki Saeki, Yuki Saito, Shinnosuke Takamichi, and Hiroshi Saruwatari
Lifter training and sub-band modeling for computationally efficient and high-quality voice conversion using spectral differentials
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
[IEEE Xplore] [arXiv] [slide] [video]
Domestic conferences (non-reviewed)
- Takaaki Saeki, Yuki Saito, Shinnosuke Takamichi, and Hiroshi Saruwatari
Implementation and evaluation of real-time full-band DNN-based voice conversion based on sub-band filtering
ASJ, Autumn meeting, 2020. (in Japanese)
[pdf] [slide] - Takaaki Saeki, Yuki Saito, Shinnosuke Takamichi, and Hiroshi Saruwatari
Sub-band lifter-training method for full-band voice conversion using spectral differentials
ASJ, Spring meeting, 2020. (in Japanese)
[pdf] - Takaaki Saeki, Yuki Saito, Shinnosuke Takamichi, and Hiroshi Saruwatari
Lifter training and sub-band modelling for DNN-based voice conversion using spectral differentials
IPSJ SIG Technical Report, 2020. (in Japanese)
[pdf] [slide] - Takaaki Saeki, Yuki Saito, Shinnosuke Takamichi, and Hiroshi Saruwatari
Filter Estimation for Computational Complexity Reduction of DNN-based Voice Conversion Using Spectral Differentials
ASJ Autumn meeting, 2019. (in Japanese)
[pdf]