Leveraging Contrastive Learning and Self-Training for Multimodal Emotion
Recognition with Limited Labeled Samples
Leveraging Contrastive Learning and Self-Training for Multimodal Emotion
Recognition with Limited Labeled Samples
The Multimodal Emotion Recognition challenge MER2024 focuses on recognizing emotions using audio, language, and visual signals. In this paper, we present our submission solutions for the Semi-Supervised Learning Sub-Challenge (MER2024-SEMI), which tackles the issue of limited annotated data in emotion recognition. Firstly, to address the class imbalance, we adopt an …