DocumentCode
1977483
Title
Bimodal emotion recognition
Author
De Silva, Liyanage C. ; Ng, Pei Chi
Author_Institution
Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore
fYear
2000
fDate
2000
Firstpage
332
Lastpage
335
Abstract
This paper describes the use of statistical techniques and hidden Markov models (HMM) in the recognition of emotions. The method aims to classify 6 basic emotions (anger, dislike, fear, happiness, sadness and surprise) from both facial expressions (video) and emotional speech (audio). The emotions of 2 human subjects were recorded and analyzed. The findings show that the audio and video information can be combined using a rule-based system to improve the recognition rate
Keywords
face recognition; hidden Markov models; knowledge based systems; pattern classification; speech recognition; statistical analysis; HMM; audio; bimodal emotion recognition; classification; emotional speech; facial expressions; hidden Markov models; rule-based system; statistical techniques; video; Electrical capacitance tomography; Emotion recognition; Face recognition; Hidden Markov models; Humans; Image databases; Image sequences; Signal processing algorithms; Speech recognition; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Automatic Face and Gesture Recognition, 2000. Proceedings. Fourth IEEE International Conference on
Conference_Location
Grenoble
Print_ISBN
0-7695-0580-5
Type
conf
DOI
10.1109/AFGR.2000.840655
Filename
840655
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