Syed Riyas Ahamed

Abstract Understanding emotions in dialogue is essential for socially intelligent agents; however, the challenge in multimodal approaches comes from the combination of multiple modalities of speech, language, and visual expressions. In this paper, we propose an experimental benchmark of four well-known multimodal fusion techniques: early fusion, late fusion, hybrid averaging, and meta fusion for the MELD dataset based on frozen pretrained encoders for multimodal emotion recognition.