Speaker Independent Emotion Recognition Using HMMs Fusion System with Relative Features

摘要：

Speaker Independent Emotion Recognition is particularly difficult for the individual differences of acoustic character and culture background.So,relative features obtained by calculating the features change of emotion speech relative to natural speech are adopted to weaken the influence from the individual differences in the paper.Moreover,an improved ranked voting fusion system is proposed to combine the decisions from four hidden Markov model(HMM)classifiers which are based on different feature vectors respectively.The recognition results of the provided algorithm have been compared with the isolated HMMs with absolute features,by Berlin database of emotional speech,and the average recognition rate has reached 78.4％ in speaker independent case.

作者: Liqin Fu Xia Mao Lijiang Chen

作者单位: School of Electronic and Information Engineering,Beihang University,Beijing,CHINA

会议类型: 国际会议

会议名称: 第一届智能网络与智能系统国际会议(ICINIS 2008)(The First International Conference on Intelligent Networks and Intelligent Systems)

会议地点: 武汉

会议语种:英文

在线出版日期: 2008-11-01（万方平台首次上网日期，不代表论文的发表时间）