EEG-based emotion recognition in music listening: A comparison of schemes for multiclass support vector machine

Authors:
Yuan-Pin Lin;Chi-Hong Wang;Tien-Lin Wu;Shyh-Kang Jeng;Jyh-Horng Chen
Affiliations:
Department of Electrical Engineering, National Taiwan University, Taiwan;Cardinal Tien Hospital, Yung-Ho Branch, Taiwan;Department of Electrical Engineering, National Taiwan University, Taiwan;Department of Electrical Engineering, National Taiwan University, Taiwan;Department of Electrical Engineering, National Taiwan University, Taiwan
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

Citing 0
Cited 5

Real-time EEG-based emotion recognition and its applications

Transactions on computational science XII
First demonstration of a musical emotion BCI

ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Machine Recognition of Music Emotion: A Review

ACM Transactions on Intelligent Systems and Technology (TIST)
Valence, arousal and dominance in the EEG during game play

International Journal of Autonomous and Adaptive Communications Systems
Human-centric music medical therapy exploration system

Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

Currently, how to equip machines with the ability for properly recognizing users' felt-emotion during multimedia presentation is a growing issue. In this study we focused on the approach for recognizing music-induced emotional responses from brain activity. A comparative study was conducted to testify the feasibility of using hierarchical binary classifiers to improve the classification performance as compared with nonhierarchical schemes. According to our classification results, we not only found that using one-against-one scheme of hierarchical binary classifier results in an improvement to performance, but also established an alternative solution for emotion recognition by proposed model-based scheme depending on 2D emotion model.