Combining emotional history through multimodal fusion methods

Continuity, one of the important characteristics of emotion, implies us that the emotional history may provide useful information for emotion recognition. Meanwhile, classification-based multimodal fusion methods show effective results in multimedia analysis tasks. In this study, two-stage classification method is proposed and emotional history is combined by the support vector machine fusion method. Evaluations on the Audio Sub-Challenge of the 2011 Audio/Visual Emotion Challenge dataset show that: (i) combining emotional history to recognition improves the accuracy significantly, (ii) classification-based multimodal fusion methods can effectively combine emotional history.