Speech Emotion Recognition Based on Rough Set and SVM

摘要：

Speech emotion recognition is becoming more and more important in such computer application fields as health care, children education, etc. There are a few works have been done on speech emotion recognition using such methods as ANN, SVM, etc in the last years. Traditional feature selection method used in speech emotion recognition is computationally too expensive to determine an optimum or suboptimum feature subset. In this paper, a novel approach based on rough set theory and SVM for speech emotion recognition is proposed. The experiment results show this approach can reduce the calculation cost while keeping high recognition rate.

关键词： Speech Emotion Recognition Rough Set Feature Selection SVM

作者: Jian Zhou Guoyin Wang Yong Yang Peijun Chen

作者单位: School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 610031,P.R.Chi Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications,

会议类型: 国际会议

会议名称: Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

会议地点: 北京

会议语种:英文

页码: 53-61

在线出版日期: 2006-07-17（万方平台首次上网日期，不代表论文的发表时间）