DocumentCode :
3781806
Title :
Emotion Recognition in Speech Using Multi-classification SVM
Author :
Weishan Zhang;Xin Meng;Zhongwei Li;Qinghua Lu;Shaochao Tan
Author_Institution :
Dept. of Software Eng., China Univ. of Pet., Qingdao, China
fYear :
2015
Firstpage :
1181
Lastpage :
1186
Abstract :
In order to improve the accuracy of emotion recognition in speech effectively, this paper proposes an emotion recognition algorithm based on SVM classification algorithm. Firstly, we use the SVM multi-class classification algorithm to optimize the parameters of penalty factor and kernel function. Then we use the optimized parameters to realize emotion recognition. Finally we obtain the accuracy of each kind of emotion using the Chinese emotional data set, using a variety of multi classification algorithm based on SVM. The emotion recognition can reach the highest rate of 96.00%.
Keywords :
"Support vector machines","Emotion recognition","Speech","Speech recognition","Kernel","Classification algorithms","Training"
Publisher :
ieee
Conference_Titel :
Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015 IEEE 12th Intl Conf on
Type :
conf
DOI :
10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.215
Filename :
7518394
Link To Document :
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