A Data Driven Emotion Recognition Method Based on Rough Set Theory

Authors:
Yong Yang;Guoyin Wang;Fei Luo;Zhenjing Li
Affiliations:
School of Information Science and Technology, Southwest Jiaotong University, Chengdou, P.R. China 610031 and Institute of Computer Science & Technology, Chongqing University of Posts and Telecommu ...;Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China 400065;Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China 400065;Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China 400065
Venue:
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Year:
2008

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Abstract

Affective computing is becoming a more and more important topic in intelligent computing technology. Emotion recognition is one of the most important topics in affective computing. It is always performed on face and voice information with such technology as ANN, fuzzy set, SVM, HMM, etc. In this paper, based on the idea of data driven data mining and rough set theory, a novel emotion recognition method is proposed. Firstly, an information system including facial features is taken as a tolerance relation in rough set, based on the idea of data driven data mining, a suitable threshold is selected for the tolerance relation. Then a reduction algorithm based on condition entropy is proposed for the tolerance relation, SVM is taken as the final classifier. Simulation experiment results show that the proposed method can use less features and get higher recognition rate, and the proposed method is proved effective and efficient.