Wed, 20 Aug 2008 22:20:40 BST CiteULike: tessaverhoef audio http://www.citeulike.org/user/tessaverhoef/tag/audio CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/tessaverhoef/article/1296328 <i>Multimedia, IEEE Transactions on, Vol. 9, No. 2. (2007), pp. 424-428.</i><br /><br />The ability of a computer to detect and appropriately respond to changes in a user's affective state has significant implications to human-computer interaction (HCI). In this paper, we present our efforts toward audio-visual affect recognition on 11 affective states customized for HCI application (four cognitive/motivational and seven basic affective states) of 20 nonactor subjects. A smoothing method is proposed to reduce the detrimental influence of speech on facial expression recognition. The feature selection analysis shows that subjects are prone to use brow movement in face, pitch and energy in prosody to express their affects while speaking. For person-dependent recognition, we apply the voting method to combine the frame-based classification results from both audio and visual channels. The result shows 7.5% improvement over the best unimodal performance. For person-independent test, we apply multistream HMM to combine the information from multiple component streams. This test shows 6.1% improvement over the best component performance Audio-Visual Affect Recognition Zhihong Zeng Jilin Tu Ming Liu Thomas Huang Brian Pianfetti Dan Roth Stephen Levinson doi:10.1109/TMM.2006.886310 Multimedia, IEEE Transactions on, Vol. 9, No. 2. (2007), pp. 424-428. 2007-05-15T02:33:24-00:00 2007 Multimedia, IEEE Transactions on 9 2 424 428 affect audio bimodal hmm naturalistic recognition video