OTTers: One-turn topic transitions for open-domain dialogue

Karin Sevegnani, David M. Howcroft, Ioannis Konstas, Verena Rieser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

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.

Original languageEnglish
Title of host publication59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference
PublisherAssociation for Computational Linguistics
Pages2492-2504
Number of pages13
Volume1
ISBN (Electronic)9781954085527
DOIs
Publication statusPublished - Aug 2021
EventJoint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing - Virtual, Online
Duration: 1 Aug 20216 Aug 2021

Conference

ConferenceJoint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing
Abbreviated titleACL-IJCNLP 2021
CityVirtual, Online
Period1/08/216/08/21

ASJC Scopus subject areas

  • Software
  • Computational Theory and Mathematics
  • Linguistics and Language
  • Language and Linguistics

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