Peking Opera Synthesis via Duration Informed Attention Network

Yusong Wu, Shengchen Li, Chengzhu Yu, Heng Lu, Chao Weng, Liqiang Zhang, Dong Yu


Peking Opera has been the most dominant form of Chinese performing art since around 200 years ago. A Peking Opera singer usually exhibits a very strong personal style via introducing improvisation and expressiveness on stage which leads the actual rhythm and pitch contour to deviate significantly from the original music score. This inconsistency poses a great challenge in Peking Opera singing voice synthesis from a music score. In this work, we propose to deal with this issue and synthesize expressive Peking Opera singing from the music score based on the Duration Informed Attention Network (DurIAN) framework. To tackle the rhythm mismatch, Lagrange multiplier is used to find the optimal output phoneme duration sequence with the constraint of the given note duration from music score. As for the pitch contour mismatch, instead of directly inferring from music score, we adopt a pseudo music score generated from the real singing and feed it as input during training. The experiments demonstrate that with the proposed system we can synthesize Peking Opera singing voice with high-quality timbre, pitch and expressiveness.


 DOI: 10.21437/Interspeech.2020-1724

Cite as: Wu, Y., Li, S., Yu, C., Lu, H., Weng, C., Zhang, L., Yu, D. (2020) Peking Opera Synthesis via Duration Informed Attention Network. Proc. Interspeech 2020, 1226-1230, DOI: 10.21437/Interspeech.2020-1724.


@inproceedings{Wu2020,
  author={Yusong Wu and Shengchen Li and Chengzhu Yu and Heng Lu and Chao Weng and Liqiang Zhang and Dong Yu},
  title={{Peking Opera Synthesis via Duration Informed Attention Network}},
  year=2020,
  booktitle={Proc. Interspeech 2020},
  pages={1226--1230},
  doi={10.21437/Interspeech.2020-1724},
  url={http://dx.doi.org/10.21437/Interspeech.2020-1724}
}