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Emotion Recognition Method Based on Multimodal Sensor Fusion Algorithm
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  • Emotion Recognition Method Based on Multimodal Sensor Fusion Algorithm
  • Emotion Recognition Method Based on Multimodal Sensor Fusion Algorithm
저자명
Moon. Byung-Hyun,Sim. Kwee-Bo
간행물명
International journal of fuzzy logic and intelligent systems
권/호정보
2008년|8권 2호|pp.105-110 (6 pages)
발행정보
한국지능시스템학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.