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Let's Talk! Striking Up Conversations via Conversational Visual Question Generation

2022-05-19 05:32:26
Shih-Han Chan, Tsai-Lun Yang, Yun-Wei Chu, Chi-Yang Hsu, Ting-Hao Huang, Yu-Shian Chiu, Lun-Wei Ku

Abstract

An engaging and provocative question can open up a great conversation. In this work, we explore a novel scenario: a conversation agent views a set of the user's photos (for example, from social media platforms) and asks an engaging question to initiate a conversation with the user. The existing vision-to-question models mostly generate tedious and obvious questions, which might not be ideals conversation starters. This paper introduces a two-phase framework that first generates a visual story for the photo set and then uses the story to produce an interesting question. The human evaluation shows that our framework generates more response-provoking questions for starting conversations than other vision-to-question baselines.

Abstract (translated)

URL

https://arxiv.org/abs/2205.09327

PDF

https://arxiv.org/pdf/2205.09327.pdf


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