GIA-MIC reports 80.7% weighted accuracy on IEMOCAP emotion recognition by combining gated interactive cross-attention with a modality-invariant KL-divergence constraint.
In contrast, with temporal modality-invariant constraints (γ̸= 0), the three modalities exhibit greater overlap, indicating increased shared information
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GIA-MIC: Multimodal Emotion Recognition with Gated Interactive Attention and Modality-Invariant Learning Constraints
GIA-MIC reports 80.7% weighted accuracy on IEMOCAP emotion recognition by combining gated interactive cross-attention with a modality-invariant KL-divergence constraint.