关键词: 模糊认知图, 语音情感识别, 决策级融合, 特征级融合

Abstract: Fuzzy Cognitive Map（FCM） as a graph method analysis has application in the aspect of data classification. In order to improve the classification accuracy of speech emotion recognition and retain its advantage of the training speed, after a detailed analysis of feature level fusion and decision level fusion, fusion of FCM is proposed. To implement decision level fusion FCM, the numeric outputs of FCM is transformed to the probabilistic outputs, supplied a unified outputs for different input feature. On this basis, an adaptive weighted fusion method is introduced, which considers fully the difference accuracy rates of different features without the prior knowledge and subjective definition. Simulation experiments verify the correctness of the fusion FCM method. Compared to the traditional FCM and Support Vector Machine（SVM）, the proposed method has a higher recognition rate and greatly reduces the confusion level between the emotional.

Key words: Fuzzy Cognitive Map（FCM）, speech emotion recognition, decision level fusion, feature level fusion