Paper: Importance-Driven Turn-Bidding for Spoken Dialogue Systems

ACL ID P10-1019
Title Importance-Driven Turn-Bidding for Spoken Dialogue Systems
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010

Current turn-taking approaches for spoken dialogue systems rely on the speaker re- leasing the turn before the other can take it. This reliance results in restricted interac- tions that can lead to inefficient dialogues. In this paper we present a model we re- fer to as Importance-Driven Turn-Bidding that treats turn-taking as a negotiative pro- cess. 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 turn- taking approaches in an artificial collabo- rative slot-filling domain. The negotiative nature of this model creates efficient dia- logues, and supports the improvement of mixed-initiative interaction.