Interpretable multimodal sentiment analysis based on textual modality descriptions by using large-scale language models

Understand

Multimodal sentiment analysis is an important area for understanding the user's internal states.

• Deep learning methods were effective, but the problem of poor interpretability has gradually gained attention.
• Previous works have attempted to use attention weights or vector distributions to provide interpretability.
• However, their explanations were not intuitive and can be influenced by different trained models.