SCANET: Improving multimodal representation and fusion with sparse‐ and cross‐attention for multimodal sentiment analysis

• Published in: Computer animation and virtual worlds Vol. 33; no. 3-4
• Main Authors: Wang, Hao, Yang, Mingchuan, Li, Zheng, Liu, Zhenhua, Hu, Jie, Fu, Ziwang, Liu, Feng
• Format: Journal Article
• Language: English
• Published: Chichester Wiley Subscription Services, Inc 01.06.2022
• Subjects: Asymmetry; Audio data; cross‐modal attention; Data mining; Learning; multimodal fusion; multimodal sentiment analysis; Performance enhancement; Representations; Sentiment analysis; sparse transformer

Learning unimodal representations and improving multimodal fusion are two cores of multimodal sentiment analysis (MSA). However, previous methods ignore the information differences between different modalities: Text modality has high‐order semantic features than other modalities. In this article, we...