Multimodal Fusion of EEG and Musical Features in Music-Emotion Recognition
DOI:
https://doi.org/10.1609/aaai.v31i1.11112Keywords:
emotion recognition, affective computing, brain-computer interfaceAbstract
Multimodality has been recently exploited to overcome the challenges of emotion recognition. In this paper, we present a study of fusion of electroencephalogram (EEG) features and musical features extracted from musical stimuli at decision level in recognizing the time-varying binary classes of arousal and valence. Our empirical results demonstrate that EEG modality was suffered from the non-stability of EEG signals, yet fusing with music modality could alleviate the issue and enhance the performance of emotion recognition.
Downloads
Published
2017-02-12
How to Cite
Thammasan, N., Fukui, K.- ichi, & Numao, M. (2017). Multimodal Fusion of EEG and Musical Features in Music-Emotion Recognition. Proceedings of the AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.11112
Issue
Section
Student Abstract Track