Development of Interactive Feature Selection Algorithm(IFS) for Emotion Recognition

• Published in: International Journal of Fuzzy Logic and Intelligent systems, 6(4) Vol. 6; no. 4; pp. 282 - 287
• Main Authors: Yang, Hyun-Chang, Kim, Ho-Duck, Park, Chang-Hyun, Sim, Kwee-Bo
• Format: Journal Article
• Language: Korean
• Published: 한국지능시스템학회 01.12.2006
• Subjects: 전기공학; SFS; Feature selection; GAFS; IFS; Reinforcement Learning; Emotion; Recognition
• ISSN: 1598-2645; 2093-744X

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