期刊论文

Chen, Zengzhao(zzchen@ccnu.edu.cn)

英文

Expert Systems with Applications

0957-4174

2023

214

118943

10.1016/j.eswa.2022.118943

The authors thank the editor and anonymous reviewers for their valuable suggestions. This work has been supported by the National Natural Science Foundation of China (Grant No. 62077022 , 61875068 , 62211530433 , 62177018 , 62011530436 , 62277041 , 62005092 , 62077020 ), the National Teacher Development Collaborative Innovation Experimental Base Construction Research Project of Central China Normal University (No. CCNUTEIII 2021-21 ), and the National Key R&D Program of China ( 2021YFC3340802 ). We would like to thank Dr. Tingting Liu and Prof. Zhaoli Zhang for assistance in advice.

本校为第一机构

Speech emotion recognition (SER) has become a crucial topic in the field of human–computer interactions. Feature representation plays an important role in SER, but there are still many challenges in feature representation such as the inability to predict which features are most effective for SER and the cultural differences in emotion expression. Most previous studies use a single type of feature for the recognition task or conduct early fusion of features. However, a single type of feature cannot well reflect the emotions of speech signals. A...