Automatic hierarchical classification of emotional speech

作者：Xiao Zhongzhe^*; Dellandrea Emmanuel; Dou Weibei; Chen Liming

来源：ISM Workshops 2007 - 9th IEEE International Symposium on Multimedia - Workshops, 2007-12-10 to 2007-12-12.

DOI：10.1109/ISMW.2007.4475985

• Automatic analysis
• Emotional speech
• Evidence theory
• Feature selection
• Hierarchical classifications
• Hierarchical classifiers
• Human-computer
• International symposium
• Multimedia indexing
• Recognition rates
• Semantic information
• Speech emotion classification

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%.

• 出版日期2007
• 单位Ecole Centrale de Lyon