Reactive Multi-Stage Feature Fusion for Multimodal Dialogue Modeling

This paper is published in the 7th Dialog System Technology Challenge (DSTC7) in the Proceedings of Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019 - DSTC7).

Full paper: Here

Visual question answering and visual dialogue tasks have been increasingly studied in the multimodal field towards more practical real-world scenarios. A more challenging task, audio visual scene-aware dialogue (AVSD), is proposed to further advance the technologies that connect audio, vision, and language, which introduces temporal video information and dialogue interactions between a questioner and an answerer. This paper proposes an intuitive mechanism that fuses features and attention in multiple stages in order to well integrate multimodal features, and the results demonstrate its capability in the experiments. Also, we apply several state-of-the-art models in other tasks to the AVSD task, and further analyze their generalization across different tasks.

PhD candidate at National Taiwan University, research interests cover Natural Language Processing, and Dialogue Systems.
Shang-Yu Su