| Paper ID | SPE-16.3 |
| Paper Title |
A CHAPTER-WISE UNDERSTANDING SYSTEM FOR TEXT-TO-SPEECH IN CHINESE NOVELS |
| Authors |
Junjie Pan, Lin Wu, Xiang Yin, Pengfei Wu, Chenchang Xu, Zejun Ma, Bytedance, China |
| Session | SPE-16: Speech Synthesis 4: Front-end |
| Location | Gather.Town |
| Session Time: | Wednesday, 09 June, 13:00 - 13:45 |
| Presentation Time: | Wednesday, 09 June, 13:00 - 13:45 |
| Presentation |
Poster
|
| Topic |
Speech Processing: [SPE-SYNT] Speech Synthesis and Generation |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
In TTS-based audiobook production, multi-role dubbing and emotional expressions can significantly improve the naturalness of audiobooks. However, it requires manual annotation of original novels with explicit speaker and emotion tags in sentence level, which is extremely time-consuming and costly. In this paper, we proposes a chapter-wise understanding system for Chinese novels, to predict speaker and emotion tags automatically based on the chapter-level context. Compared with baselines of each component, our models obtain higher performance. Audiobooks produced by our proposed system along with a multi-speaker emotional TTS system, are proved to achieve comparable quality score to audiobooks made by individual producers. Demos are demonstrated in https://jeffpan.net/icassp/2021/main.html. |
