Hyper-MML integrates EEG, audio, and video using an Adaptive Brain Encoder with Mutual-cross Attention (ABEMA) and Adaptive Hypergraph Fusion Module (AHFM) to outperform prior methods on EAV and AFFEC datasets for conversational emotion recognition.
An efficient graph learning system for emotion recognition inspired by the cognitive prior graph of eeg brain network
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Hypergraph Multi-Modal Learning for EEG-based Emotion Recognition in Conversation
Hyper-MML integrates EEG, audio, and video using an Adaptive Brain Encoder with Mutual-cross Attention (ABEMA) and Adaptive Hypergraph Fusion Module (AHFM) to outperform prior methods on EAV and AFFEC datasets for conversational emotion recognition.