SPEECH EMOTION RECOGNITION USING RBF KERNEL OF LIBSVM

被引：0
|
作者：
Chavhan, Y. D. [1 ]
Yelure, B. S. [1 ]
Tayade, K. N. [1 ]
机构：
[1] GCE, Karad, Karad, India
来源：
2015 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS AND COMMUNICATION SYSTEMS (ICECS) | 2015年
关键词：
Speech emotion; Emotion Recognition; LIBSVM; MFCC and MEDC; RBF;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Automatic Speech Emotion Recognition (SER) is a current research topic in the field of Human Computer Interaction (HCI) with wide range of applications. The speech features such as, Mel Frequency cepstrum coefficients (MFCC) and Mel Energy Spectrum Dynamic Coefficients (MEDC) are extracted from speech utterance. The LIBSVM is used as classifier to identify different emotional states such as anger, happiness, sadness, neutral, fear, from Berlin emotional database. The results are taken by using RBF kernel of LIBSVM. It gives 93.75% recognition accuracy for RBF kernel.
引用
收藏
页码：1132 / 1135
页数：4
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