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DOI码：10.1109/ISM.Workshops.2007.56

发表刊物：9th IEEE International Symposium on Multimedia9th IEEE International Symposium on Multimedia

摘要：Speech emotion is high semantic information and its automatic analysis may have many applications such as smart human-computer interactions or multimedia indexing. As a pattern recognition problem, the feature selection and the structure of the classifier are two important aspects for automatic speech emotion classification. In this paper, we propose a novel feature selection scheme based on the evidence theory. Furthermore, we also present a new automatic approach for constructing a hierarchical classifier, which allows better performance than a global classifier as it is mostly used in the literature. Experimented on the Berlin database, our approach showed its effectiveness, scoring a recognition rate up to 78.64%.

合写作者：Dellandrea, Emmanuel, Dou, Weibei, Chen, Liming,Dou, Weibei, Chen, Liming

第一作者：Xiao, Zhongzhe,Zhang, Bin, Dou, Weibei, Chen, Liming

论文类型：会议论文

页面范围：291

是否译文：否

发表时间：2007-12-10