Title :
Remarks on emotion recognition from multi-modal bio-potential signals
Author :
Takahashi, Kazuhiko ; Tsukaguchi, Akinori
Author_Institution :
Yamaguchi Univ., Japan
Abstract :
This paper proposes an emotion recognition system from multi-modal bio-potential signals. For emotion recognition, two types of classifier: neural network (NN) and support vector machine (SVM) are designed and investigated. Using gathered data under psychological emotion stimulation experiments, the classifiers are trained and tested. In experiments of recognizing two emotion: pleasure and unpleasure, recognition rates of 62.3% with the NN classifier and 59.7% with the SVM classifier are achieved. The experimental result shows that using multi-modal bio-potential signals is feasible and that NN and/or SVM are well suited for emotion recognition tasks.
Keywords :
emotion recognition; learning (artificial intelligence); pattern classification; psychology; support vector machines; NN classifier; SVM classifier; emotion recognition system; learning (artificial intelligence); multimodal biopotential signals; neural network; psychological emotion stimulation; support vector machine; Biological neural networks; Emotion recognition; Face recognition; Humans; Neural networks; Psychology; Speech recognition; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Systems, Man and Cybernetics, 2003. IEEE International Conference on
Print_ISBN :
0-7803-7952-7
DOI :
10.1109/ICSMC.2003.1244650