@inproceedings{4bbfdc58c0ef457199602e28dd4e3355,
title = "Importance-driven turn-bidding for spoken dialogue systems",
abstract = "Current turn-taking approaches for spoken dialogue systems rely on the speaker releasing the turn before the other can take it. This reliance results in restricted interactions that can lead to inefficient dialogues. In this paper we present a model we refer to as Importance-Driven Turn-Bidding that treats turn-taking as a negotiative process. Each conversant bids for the turn based on the importance of the intended utterance, and Reinforcement Learning is used to indirectly learn this parameter. We find that Importance-Driven Turn-Bidding performs better than two current turntaking approaches in an artificial collaborative slot-filling domain. The negotiative nature of this model creates efficient dialogues, and supports the improvement of mixed-initiative interaction.",
author = "Selfridge, \{Ethan O.\} and Heeman, \{Peter A.\}",
note = "Publisher Copyright: {\textcopyright} 2010 Association for Computational Linguistics.; 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010 ; Conference date: 11-07-2010 Through 16-07-2010",
year = "2010",
language = "English (US)",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "177--185",
editor = "Jan Hajic and Sandra Carberry and Stephen Clark",
booktitle = "ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, Conference Proceedings",
}