Previous studies in multimodal emotion recognition have not adequately addressed the disparity between unimodal expression and multimodal perception in emotion labeling, nor have they optimized multim
Multimodal emotion recognition leverages multiple modalities to capture emotional cues more comprehensively, thereby improving the accuracy and robustness of emotion recognition. From the perspective
Loughborough University Multimodal Emotion Database-2 (LUMED-2) is a new multimodal emotion dataset that was created by the researchers of Loughborough University, UK, and Hacettepe University, Turkey
Both facial expression and tone of voice represent key signals of emotional communication but their brain processing correlates remain unclear. Accordingly, we constructed a novel implicit emotion rec