Improving Context Modelling in Multimodal Dialogue Generation

Shubham Agarwal; Ondrej Dusek; Ioannis Konstas; Verena Rieser

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arXiv · 1810.11955

Improving Context Modelling in Multimodal Dialogue Generation

Shubham Agarwal·Ondrej Dusek·Ioannis Konstas·Verena Rieser

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Abstract

In this work, we investigate the task of textual response generation in a multimodal task-oriented dialogue system. Our work is based on the recently released Multimodal Dialogue (MMD) dataset (Saha et al., 2017) in the fashion domain. We introduce a multimodal extension to the Hierarchical Recurrent Encoder-Decoder (HRED) model and show that this extension outperforms strong baselines in terms of text-based similarity metrics. We also showcase the shortcomings of current vision and language models by performing an error analysis on our system's output.

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Shubham Agarwal, Ondrej Dusek, Ioannis Konstas, Verena Rieser. 2018-10-20. Improving Context Modelling in Multimodal Dialogue Generation. https://arxiv.org/abs/1810.11955

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