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

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...

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Hauptverfasser: Chan, Shih-Han, Yang, Tsai-Lun, Chu, Yun-Wei, Hsu, Chi-Yang, Huang, Ting-Hao, Chiu, Yu-Shian, Ku, Lun-Wei
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Sprache:eng
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Zusammenfassung: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.
DOI:10.48550/arxiv.2205.09327