关键词: 特征选择, F-score, 互信息, 支持向量机, 语音情感识别

Abstract: For the F-score feature selection algorithm can not reveal the mutual information among features, the method of removing the redundancy is applied to improve the F-score algorithm. Using the German emotional speech database EMO-DB, based on the extraction of speech emotion features, the paper uses the classification accuracy of SVM to choose the best feature subset. Compared with the F-score method, the improved feature selection algorithm can achieve dimension reduction substantially, select an effective feature subset, and obtain an ideal speech emotion recognition accuracy.

Key words: feature selection, F-score, mutual information, Support Vector Machine（SVM）, speech emotion recognition