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Cross-Modal Emotion Understanding: A Transformer-GAT Approach for Dialogue Emotion Recognition

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

Multimodal emotion recognition is a key research area in affective computing, with applications in sentiment analysis, intelligent customer service, and human-computer interaction. However, existing methods often rely on single-modal features or simple multimodal fusion, failing to capture the synergy between global and local contexts, which limits model performance and emotion understanding. To address this challenge, we propose Transformer-GAT, a hybrid framework that combines Transformer and the Graph Attention Network to enable cross-modal emotion understanding. The Transformer is used to

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