基于情感上下文的语音情感推理算法

Emotion Reasoning Algorithm Based on Emotional Context of Speech

针对前后相邻情感语句的情感变化存在相互关联的特性,提出基于情感上下文的情感推理算法.该算法首先利用传统语音情感特征和上下文语音情感特征分别识别待分析情感语句的情感状态,然后借助情感交互矩阵及两类情感特征识别结果的置信度对待测试语句的情感状态进行融合推理.在此基础上,建立语音情感上下文推理规则,利用该规则根据相邻语句的情感状态对待分析情感语句情感状态进行调整,最终得出待分析情感语句所属的情感类别.在自行录制的包含6种基本情感数据库上的实验结果表明,与仅采用声学特征的方法相比,文中提出方法平均识别率提高12.17%.

Since the change of emotion state is continuous in daily conversations,an emotion reasoning algorithm based on emotional context for speech emotion recognition（ SER） is put forward. In this algorithm,contextual speech emotion features and widely-used acoustic speech emotion features are used to recognize emotion state in continuous speech utterances respectively. Then,the emotional interaction matrix and the confidence coefficient are used to fuse the recognition results of these two kinds of features. Finally,the emotion reasoning rule based on the emotional context is proposed to adjust the fusion results according to the emotional context of the emotional utterance to be analyzed. The fusion results after adjusting are used as the emotion state of the emotional utterance to be analyzed. The experimental results on the recorded emotional speech corpus with respect to 6 basic emotion states show that the proposed algorithm can improve the emotion recognition accuracies of the continuous speech,and compared with the method by widely-used acoustic speech emotional features,the average recognition accuracy of the proposed algorithm rises by 12. 17%.