tailieunhanh - Báo cáo khoa học: "Importance-Driven Turn-Bidding for Spoken Dialogue Systems"

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. . | Importance-Driven lUrn-Bidding for Spoken Dialogue Systems Ethan O. Selfridge and Peter A. Heeman Center for Spoken Language Understanding Oregon Health Science University 20000 nW Walker Rd. Beaverton OR 97006 selfridg@ heemanp@ 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. 1 Introduction As spoken dialogue systems are designed to perform ever more elaborate tasks the need for mixed-initiative interaction necessarily grows. Mixed-initiative interaction where agents both artificial and human may freely contribute to reach a solution efficiently has long been a focus of dialogue systems research Allen et al. 1999 Guinn 1996 . Simple slot-filling tasks might not require the flexible environment that mixed-initiative interaction brings but those of greater complexity such as collaborative task completion or long-term planning certainly do Ferguson et al. 1996 . However translating this interaction into working systems has proved problematic Walker et al. 1997 in part to issues surrounding turn-taking the transition from one speaker to another. Many computational turn-taking approaches seek to minimize silence and utterance overlap during transitions. This leads to the speaker controlling the turn transition. For example .