Emotion Recognition in Speech using Multi-Classification SVM

被引：4
|
作者：
Zhang, Weishan [1 ]
Meng, Xin [1 ]
Li, Zhongwei [1 ]
Lu, Qinghua [1 ,2 ]
Tan, Shaochao [1 ]
机构：
[1] China Univ Petr, Dept Software Engn, 66 Changjiang West Rd, Qingdao 266580, Peoples R China
[2] Natl ICT Australia, Software Syst Res Grp, Sydney, NSW, Australia
来源：
IEEE 12TH INT CONF UBIQUITOUS INTELLIGENCE & COMP/IEEE 12TH INT CONF ADV & TRUSTED COMP/IEEE 15TH INT CONF SCALABLE COMP & COMMUN/IEEE INT CONF CLOUD & BIG DATA COMP/IEEE INT CONF INTERNET PEOPLE AND ASSOCIATED SYMPOSIA/WORKSHOPS | 2015年
基金：
中国国家自然科学基金;
关键词：
SVM; multi class classification algorithm; emotion recognition; parameter optimization;
D O I：
10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.215
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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%.
引用
收藏
页码：1181 / 1186
页数：6
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