The development of interactive feature selection and GA feature selection method for emotion recognition

Authors:
Kwee-Bo Sim;In-Hun Jang;Chang-Hyun Park
Affiliations:
School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea;School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea;School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, Korea
Venue:
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Year:
2007

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Abstract

This paper presents an original feature selection method for Emotion Recognition which includes many original elements. Feature selection has some merit regarding pattern recognition performance. Thus, we developed a method called an 'Interactive Feature Selection(IFS)' and 'GA Feature Selection(GAFS)'. Afterwards, the results (selected features) of the IFS and GAFS were applied to an emotion recognition system (ERS), which was also implemented in this research. Especially, our interactive feature selection method was based on a Reinforcement Learning Algorithm since it required responses from human users. By performing the IFS, we were able to obtain three top features and apply them to the ERS. We compared those results from a random selection and Sequential Forward Selection (SFS) and Genetic Algorithm Feature Selection (GAFS).