The User Model-Based Summarize and Re_ne Approach Improves Information Presentation in Spoken Dialog Systems

Andi K. Winterboer (1) , Martin I. Tietze (2) , Maria K. Wolters (2) , Johanna D. Moore (2)

1 Advisory Board of OA Cancer
2 Institute for Communicating and Collaborative Systems

A common task for Spoken Dialogue Systems (SDS) is to help users select a suitable option (e.g., fight, hotel, restaurant) from the set of options available. As the number of options increases, the system must have strategies for generating summaries that enable the user to browse the option space e_ciently and successfully. In the user-model based summarize and refine approach (UMSR, Demberg and Moore, 2006), options are clustered to maximize utility with respect to a user model, and linguistic devices such as discourse cues and adverbials are used to highlight the trade-o_s among the presented items. In a Wizard-of-Oz experiment, we show that the UMSR approach leads to improvements in task success, e_ciency, and user satisfaction compared to an approach that clusters the available options to maximise coverage of the domain (Polifroni et al., 2003). In both a laboratory experiment and a web-based experimental paradigm employing the Amazon Mechanical Turk platform, we show that the discourse cues in UMSR summaries help users compare diffirent options and choose between options, even though they do not improve verbatim recall. This effect was observed for both written and spoken stimuli.

Mots clés: Information presentation; spoken dialog systems; user modeling; discourse; markers

Domaines: Linguistique

Andi K. Winterboer, Martin I. Tietze, Maria K. Wolters, Johanna D. Moore. The User Model-Based Summarize and Re_ne Approach Improves Information Presentation in Spoken Dialog Systems. Computer Speech and Language, 2010, 25 (2), pp.175. ⟨10.1016/j.csl.2010.04.003⟩. ⟨hal-00692184⟩