Mixed initiative in open-domain dialogue requires a system to pro-actively introduce new topics. The one-turn topic transition task explores how a system connects two topics in a cooperative and coherent manner. The goal of the task is to generate a "bridging" utterance connecting the new topic to the topic of the previous conversation turn. We are especially interested in commonsense explanations of how a new topic relates to what has been mentioned before. We first collect a new dataset of human one-turn topic transitions, which we call OTTers. We then explore different strategies used by humans when asked to complete such a task, and notice that the use of a bridging utterance to connect the two topics is the approach used the most. We finally show how existing state-of-the-art text generation models can be adapted to this task and examine the performance of these baselines on different splits of the OTTers data.
@article{arxiv.2105.13710,
title = {OTTers: One-turn Topic Transitions for Open-Domain Dialogue},
author = {Karin Sevegnani and David M. Howcroft and Ioannis Konstas and Verena Rieser},
journal= {arXiv preprint arXiv:2105.13710},
year = {2021}
}