Audio-visual based emotion recognition using tripled hidden Markov model

被引：0
|
作者：
Song, ML [1 ]
Chen, C [1 ]
You, MY [1 ]
机构：
[1] Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Peoples R China
来源：
2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL V, PROCEEDINGS: DESIGN AND IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS INDUSTRY TECHNOLOGY TRACKS MACHINE LEARNING FOR SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING SIGNAL PROCESSING FOR EDUCATION | 2004年
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Emotion recognition is one of the latest challenges in intelligent human/machine communication. Most of previous work on emotion recognition focused on extracting emotions from visual or audio information separately. A novel approach is presented in this paper to recognize the human emotion which uses both visual and audio from video clips. A tripled Hidden Markov Model is introduced to perform the recognition which allows the state asynchrony of he audio and visual observation sequences while preserving their natural correlation over time. The experimental results show that this approach outperforms only using visual or audio separately.
引用
收藏
页码：877 / 880
页数：4
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