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arXiv · 2002.06484

A Multimodal Dialogue System for Conversational Image Editing

Tzu-Hsiang Lin·Trung Bui·Doo Soon Kim·Jean Oh
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Abstract

In this paper, we present a multimodal dialogue system for Conversational Image Editing. We formulate our multimodal dialogue system as a Partially Observed Markov Decision Process (POMDP) and trained it with Deep Q-Network (DQN) and a user simulator. Our evaluation shows that the DQN policy outperforms a rule-based baseline policy, achieving 90\% success rate under high error rates. We also conducted a real user study and analyzed real user behavior.

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Tzu-Hsiang Lin, Trung Bui, Doo Soon Kim, Jean Oh. 2020-02-16. A Multimodal Dialogue System for Conversational Image Editing. https://arxiv.org/abs/2002.06484

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