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中文摘要：
提出了一种语音情感识别中特征空间的优化方法。针对情感类别两两之间的区分度,优化了情感对各自的特征空间,考察了多类分类器分解为两类分类器的方法,采用置信度判决融合的方法进行两类分类器组的重组,实验中比较了单个多类分类器和两类分类器组的识别性能。结果表明,在同等条件下性能提升了8个百分点以上,对多类分类器进行分解,优化每个情感对各自的特征空间,并进行融合的方法适合语音情感识别,对特征空间的优化效果显著。
英文摘要：
A method of optimizing feature space for speech emotion recognition is proposed.To achieve better classification between each emotion class;feature space of each pair of emotions were optimized respectively;decomposition of multi-class classifier into two-class classifiers was studied;a decision fusion technique was introduced to re-compose the two-class classifier set;recognition results of multi-class classifier and two-class classifier set were compared in a computer experiment.The results show,recognition rates were improved more than 8 percent under identical environments.The method in this paper,decomposition of multi-class classifier,optimizing feature space of each pair of emotions and decomposition using decision fusion algorithm,is suitable for speech emotion recognition and effective in optimization of feature space.
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