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.

本文介绍了 PhotoBook 数据集，该数据集是一个大规模的英语对话集合，旨在调查会话期间积累的共享对话历史。该数据集包含 2500 个对话，并建议了一个基于共同信息的基准模型，其结果表明共同信息对于解决后续描述至关重要，强调了需要开发对话交互中常用地基础的更复杂的模型。