DocumentCode :
661484
Title :
Emotion recognition from multi-modal information
Author :
Chung-Hsien Wu ; Jen-Chun Lin ; Wen-Li Wei ; Kuan-Chun Cheng
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear :
2013
fDate :
Oct. 29 2013-Nov. 1 2013
Firstpage :
1
Lastpage :
8
Abstract :
Emotion recognition is the ability to detect what people are feeling from moment to moment and to understand the connection between their feelings and verbal/non-verbal expressions. When you are aware of your emotions, you can think clearly and creatively, manage stress and challenges, communicate well with others, and display trust, empathy, and confidence. In today´s world, human-computer interaction (HCI) interface undoubtedly plays an important role in our daily life. Toward harmonious HCI interface, automated analysis of human emotion has attracted increasing attention from the researchers in multidisciplinary research fields. In this paper, we presents a survey on theoretical and practical work offering new and broad views of the latest research in emotion recognition from multi-modal information including facial and vocal expressions. A variety of theoretical background and applications ranging from salient emotional features, emotional-cognitive models, to multi-modal data fusion strategies is surveyed for emotion recognition on these modalities. Conclusions outline some of the existing emotion recognition challenges.
Keywords :
emotion recognition; human computer interaction; HCI interface; confidence; emotional cognitive models; empathy; facial expressions; human computer interaction; human emotion recognition; multimodal data fusion strategies; multimodal information; nonverbal expressions; salient emotional features; trust; verbal expressions; vocal expressions; Emotion recognition; Face recognition; Feature extraction; Hidden Markov models; Speech; Speech recognition; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific
Conference_Location :
Kaohsiung
Type :
conf
DOI :
10.1109/APSIPA.2013.6694347
Filename :
6694347
Link To Document :
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