Host: Japan Society for Fuzzy Theory and Intelligent Informatics
We focuses on emotion recognition using prosodic features in speech. There are some differences in prosodic features among indivisuals. Therefore, the accuracy of emotion recognition goes down. This paper proposes speaker adaptation technique for emotion recognition. It's an important technique that how to estimate the correct emotion of adaptation data for unsupervised speaker adaptation. The flow of conversation is usuful in estimating the emotion, because human emotion has a habit of expression continuity. So, we apply this habit to the method of emotion recognition in speech. Experimental results show the proposed technique can estimate the correct emotion of utterance data that unspecified emotional model can't estimate. Furthermore, the proposed technique shows the ability of emotion recognition technique for natural conversation.