Abstract
This paper introduces the PhotoBook dataset, a large-scale collection of visually-grounded, task-oriented dialogues in English designed to investigate shared dialogue history accumulating during conversation. Taking inspiration from seminal work on dialogue analysis, we propose a data-collection task formulated as a collaborative game prompting two online participants to refer to images utilising both their visual context as well as previously established referring expressions. We provide a detailed description of the task setup and a thorough analysis of the 2,500 dialogues collected. To further illustrate the novel features of the dataset, we propose a baseline model for reference resolution which uses a simple method to take into account shared information accumulated in a reference chain. Our results show that this information is particularly important to resolve later descriptions and underline the need to develop more sophisticated models of common ground in dialogue interaction.
Original language | English |
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Title of host publication | Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics |
Publisher | Association for Computational Linguistics |
Pages | 1895-1910 |
DOIs | |
Publication status | Published - Jul 2019 |
Event | Annual Meeting of the Association for Computational Linguistics 2019 - Florence, Italy Duration: 28 Jul 2019 → 2 Aug 2019 Conference number: 57 http://www.acl2019.org/EN/index.xhtml |
Conference
Conference | Annual Meeting of the Association for Computational Linguistics 2019 |
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Abbreviated title | ACL 2019 |
Country/Territory | Italy |
City | Florence |
Period | 28/07/19 → 2/08/19 |
Internet address |