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        <title>It’s About Time: Turn-Entry Timing For Situated Human-Robot Dialogue</title>
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    <abstract>Turn-entry timing is an important requirement for conversation, and one that spoken dialogue systems largely fail at. In this paper, we introduce a computational framework based on work from Psycholinguistics, which is aimed at achieving proper turn-taking timing for situated agents. The approach involves incremental processing and lexical prediction of the turn in progress, which allows a situated dialogue system to start its turn and initiate actions earlier than would otherwise be possible. We evaluate the framework by integrating it within a cognitive robotic architecture and testing performance on a corpus of task-oriented human-robot directives. We demonstrate that: 1) the system is superior to a non-incremental system in terms of faster responses, reduced gap between turns, and the ability to perform actions early, 2) the system can time its turn to come in immediately at a transition point or earlier to produce several types of overlap, and 3) the system is robust to various forms of disfluency in the input. Overall, this domain-independent framework can be integrated into various dialogue systems to improve responsiveness, and is a step toward more natural, human-like turn-taking behavior.</abstract>
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    <identifier type="doi">10.18653/v1/2020.sigdial-1.12</identifier>
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%0 Conference Proceedings
%T It’s About Time: Turn-Entry Timing For Situated Human-Robot Dialogue
%A Gervits, Felix
%A Thielstrom, Ravenna
%A Roque, Antonio
%A Scheutz, Matthias
%Y Pietquin, Olivier
%Y Muresan, Smaranda
%Y Chen, Vivian
%Y Kennington, Casey
%Y Vandyke, David
%Y Dethlefs, Nina
%Y Inoue, Koji
%Y Ekstedt, Erik
%Y Ultes, Stefan
%S Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2020
%8 July
%I Association for Computational Linguistics
%C 1st virtual meeting
%F gervits-etal-2020-time
%X Turn-entry timing is an important requirement for conversation, and one that spoken dialogue systems largely fail at. In this paper, we introduce a computational framework based on work from Psycholinguistics, which is aimed at achieving proper turn-taking timing for situated agents. The approach involves incremental processing and lexical prediction of the turn in progress, which allows a situated dialogue system to start its turn and initiate actions earlier than would otherwise be possible. We evaluate the framework by integrating it within a cognitive robotic architecture and testing performance on a corpus of task-oriented human-robot directives. We demonstrate that: 1) the system is superior to a non-incremental system in terms of faster responses, reduced gap between turns, and the ability to perform actions early, 2) the system can time its turn to come in immediately at a transition point or earlier to produce several types of overlap, and 3) the system is robust to various forms of disfluency in the input. Overall, this domain-independent framework can be integrated into various dialogue systems to improve responsiveness, and is a step toward more natural, human-like turn-taking behavior.
%R 10.18653/v1/2020.sigdial-1.12
%U https://aclanthology.org/2020.sigdial-1.12
%U https://doi.org/10.18653/v1/2020.sigdial-1.12
%P 86-96

Markdown (Informal)

[It’s About Time: Turn-Entry Timing For Situated Human-Robot Dialogue](https://aclanthology.org/2020.sigdial-1.12) (Gervits et al., SIGDIAL 2020)

• It’s About Time: Turn-Entry Timing For Situated Human-Robot Dialogue (Gervits et al., SIGDIAL 2020)

ACL

• Felix Gervits, Ravenna Thielstrom, Antonio Roque, and Matthias Scheutz. 2020. It’s About Time: Turn-Entry Timing For Situated Human-Robot Dialogue. In Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 86–96, 1st virtual meeting. Association for Computational Linguistics.