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 |
|---|---|
| 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 |
|---|---|
| Abbreviated title | ACL 2019 |
| Country/Territory | Italy |
| City | Florence |
| Period | 28/07/19 → 2/08/19 |
| Internet address |