Collecting Visually-Grounded Dialogue with A Game Of Sorts
This addresses the problem of unrealistic assumptions in dialogue systems for researchers, though it is incremental as it focuses on data collection rather than new models.
The paper tackles the oversimplified view of referring expressions in visually-grounded dialogue by introducing a collaborative image ranking game called 'A Game Of Sorts', resulting in a publicly available dataset and tools for studying collaborative referential processes.
An idealized, though simplistic, view of the referring expression production and grounding process in (situated) dialogue assumes that a speaker must merely appropriately specify their expression so that the target referent may be successfully identified by the addressee. However, referring in conversation is a collaborative process that cannot be aptly characterized as an exchange of minimally-specified referring expressions. Concerns have been raised regarding assumptions made by prior work on visually-grounded dialogue that reveal an oversimplified view of conversation and the referential process. We address these concerns by introducing a collaborative image ranking task, a grounded agreement game we call "A Game Of Sorts". In our game, players are tasked with reaching agreement on how to rank a set of images given some sorting criterion through a largely unrestricted, role-symmetric dialogue. By putting emphasis on the argumentation in this mixed-initiative interaction, we collect discussions that involve the collaborative referential process. We describe results of a small-scale data collection experiment with the proposed task. All discussed materials, which includes the collected data, the codebase, and a containerized version of the application, are publicly available.