Proceedings:
No. 1: Thirty-First AAAI Conference On Artificial Intelligence
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 31
Track:
Student Abstract Track
Downloads:
Abstract:
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.
DOI:
10.1609/aaai.v31i1.11112
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 31