Title :
Visual/Acoustic Emotion Recognition
Author :
Chen, Cheng-Yao ; Huang, Yue-Kai ; Cook, Perry
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ
Abstract :
To recognize and understand a person´s emotion has been known as one of the most important issue in human-computer interaction. In this paper, we present a multimodal system that supports emotion recognition from both visual and acoustic feature analysis. Our main achievement is that with this bimodal method, we can effectively extend the recognized emotion categories compared to when only visual or acoustic feature analysis works alone. We also show that by carefully cooperating bimodal features, the recognition precision of each emotion category will exceed the limit set up by the single modality, both visual and acoustic. Moreover, we believe our system is closer to real human perception and experience and hence will make emotion recognition closer to practical application in the future
Keywords :
acoustic signal processing; emotion recognition; feature extraction; human computer interaction; visual perception; acoustic emotion recognition; bimodal feature analysis; human perception; human-computer interaction; multimodal system; visual emotion recognition; Algorithm design and analysis; Computer science; Emotion recognition; Face recognition; Facial features; Feedback; Humans; Performance analysis; Robustness; Timing;
Conference_Titel :
Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-9331-7
DOI :
10.1109/ICME.2005.1521709