arXiv 2002.064842020-02-16cs.CL

A Multimodal Dialogue System for Conversational Image Editing

Carnegie Mellon University（卡内基梅隆大学）；Adobe Research（奥多比研究院）

Tzu-Hsiang Lin, Trung Bui, Doo Soon Kim, Jean Oh

备注：: Accepted at 2nd Conversational AI Workshop at NeurIPS 2018

英文摘要：

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.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。