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An Emotion Recognition Framework via Cross-modal Alignment of EEG and . . . To address this limitation, we propose an emotion recognition framework that achieves accurate multimodal alignment of Electroen-cephalogram (EEG) and eye movement data through a hybrid archi-tecture based on cross-modal attention mechanism
Cross-Modal Guiding Neural Network for Multimodal Emotion Recognition . . . This study introduces a cross-modal guiding neural network designed to fully leverage the strengths of both modalities The network includes a dual-branch feature extraction module that simultaneously extracts features from EEG and eye movement signals
Combining Eye Movements and EEG to Enhance Emotion Recognition In this paper, we adopt a multimodal emotion recognition framework by combining eye movements and EEG for three emotions (postive, negative and neutral) We explore the ef- ficient features of eye movements and EEG, and utilize the advantages of their complementary information for emotion recognition from different modality fusion strategies
Multi-modal emotion recognition using EEG and speech signals We first constructed a multi-modal and multi-environmental emotion database which includes speech, video, EEG and photoplethysmography (PPG) signals recorded from natural noisy room and anechoic chamber