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Proceedings First IEEE International Conference on Cognitive Informatics

Speech Emotion Recognition Based on Rough Set and SVM

Content Provider	IEEE Xplore Digital Library
Author	Jian Zhou Guoyin Wang Yong Yang Peijun Chen
Copyright Year	2006
Description	Author affiliation: Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu (Jian Zhou)
Abstract	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
Starting Page	53
Ending Page	61
File Size	8591031
Page Count	9
File Format	PDF
ISBN	1424404754
DOI	10.1109/COGINF.2006.365676
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Emotion recognition Support vector machines Cognitive informatics Artificial intelligence Pediatrics Humans Information processing Cognition Computer applications SVM Speech Emotion Recognition Rough Set Feature Selection
Content Type	Text
Resource Type	Article

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