Classifier Fusion for Speech Emotion Recognition

摘要：

According to multidimensional emotion space model, an improved queuing voting algorithm was proposed to implement the fusion among multiple emotion classifiers for a good emotion recognition result. Firstly, three kinds of classifier were designed based on hidden Markov model (HMM) and artificial neural network (ANN). Then, the improved queuing voting algorithm was used to fuse them. Experimental study had been carried out using Beihang University mandarin emotion speech database and Berlin database of emotional speech respectively. The results proved that the improved queuing voting algorithm can attain better fusion effect than conventional fusion algorithm and excel any single classifier evidently.

关键词： classifier fusion emotion recognition voting HMM ANN

作者: Liqin Fu Chungjiang Wang Yongmei Zhang

作者单位: National Key Laboratory for Electronic Measurement Technology,North University of China,Taiyuan, Chi School of Information Engineering North China University of Technology Beijing, China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 407-410

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）