CONCSS: Contrastive-based Context Comprehension for Dialogue-appropriate Prosody in Conversational Speech Synthesis

no code implementations • 16 Dec 2023 • Yayue Deng, Jinlong Xue, Yukang Jia, Qifei Li, Yichen Han, Fengping Wang, Yingming Gao, Dengfeng Ke, Ya Li

In this paper, we introduce a contrastive learning-based CSS framework, CONCSS.

Contrastive Learning Self-Supervised Learning +1

M2-CTTS: End-to-End Multi-scale Multi-modal Conversational Text-to-Speech Synthesis

no code implementations • 3 May 2023 • Jinlong Xue, Yayue Deng, Fengping Wang, Ya Li, Yingming Gao, JianHua Tao, Jianqing Sun, Jiaen Liang

However, it is still a challenge to comprehensively model the conversation, and a majority of conversational TTS systems only focus on extracting global information and omit local prosody features, which contain important fine-grained information like keywords and emphasis.

Speech Synthesis Text-To-Speech Synthesis

Multi-scale multi-modal micro-expression recognition algorithm based on transformer

no code implementations • 8 Jan 2023 • Fengping Wang, Jie Li, Chun Qi, Lin Wang, Pan Wang

A micro-expression is a spontaneous unconscious facial muscle movement that can reveal the true emotions people attempt to hide.

Contrastive Learning Micro Expression Recognition +2

A Dynamic 3D Spontaneous Micro-expression Database: Establishment and Evaluation

no code implementations • 31 Jul 2021 • Fengping Wang, Jie Li, Siqi Zhang, Chun Qi, Yun Zhang, Danmin Miao

Micro-expressions are spontaneous, unconscious facial movements that show people's true inner emotions and have great potential in related fields of psychological testing.