Qinghua Wu — accepted AI-conference papers

2025

DiffCSS: Diverse and Expressive Conversational Speech Synthesis with Diffusion Models

Weihao Wu, Zhiwei Lin, Yixuan Zhou, Jingbei Li, Rui Niu, Qinghua Wu +3

ICASSP 2025accepted

Conversational speech synthesis (CSS) aims to synthesize both contextually appropriate and expressive speech, and considerable efforts have been made to enhance the understanding of conversational context. However, existing CSS systems are limited to deterministic prediction, overlooking the diversi…

Cited by 0 Source ↗Scholar ↗

2022

MSDTRON: A High-Capability Multi-Speaker Speech Synthesis System for Diverse Data Using Characteristic Information

Qinghua Wu, Quanbo Shen, Jian Luan, Yujun Wang

ICASSP 2022accepted

In multi-speaker speech synthesis, data from a number of speakers usually tend to have great diversity due to the fact that the speakers may differ largely in ages, speaking styles, emotions, and so on. It is important but challenging to improve the modeling capabilities for multi-speaker speech syn…

Cited by 0 Source ↗Scholar ↗