Emotion recognition using bimodal data fusion
Dragoş Datcu, Léon J. M. Rothkrantz · 2011
This paper proposes a bimodal system for emotion recognition that uses face and speech analysis. Hidden Markov models - HMMs are used to learn and to describe the temporal dynamics of the emotion clues in the visual and acoustic channels. This approach provides a powerful method enabling to fuse the data we extract from separate modalities. The paper presents the best performing models and the results of the proposed recognition system.