The Utility of a Graphical Representation of Discourse Structure in Spoken Dialogue Systems

Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pages 360–367, Prague, Czech Republic, June 2007. c⃝2007 Association for Computational Linguistics The Utility of a Graphical Representation of Discourse Structure in Spoken Dialogue Systems Mihai Rotaru University of Pittsburgh Pittsburgh, USA mrotaru@cs.pitt.edu Diane J. Litman University of Pittsburgh Pittsburgh, USA litman@cs.pitt.edu Abstract In this paper we explore the utility of the Navigation Map (NM), a graphical repre- sentation of the discourse structure. We run a user study to investigate if users perceive the NM as helpful in a tutoring spoken dia- logue system. From the users’ perspective, our results show that the NM presence al- lows them to better identify and follow the tutoring plan and to better integrate the in- struction. It was also easier for users to concentrate and to learn from the system if the NM was present. Our preliminary analysis on objective metrics further strengthens these findings. 1 Introduction With recent advances in spoken dialogue system technologies, researchers have turned their atten- tion to more complex domains (e.g. tutoring (Litman and Silliman, 2004; Pon-Barry et al., 2006), technical support (Acomb et al., 2007), medication assistance (Allen et al., 2006)). These domains bring forward new challenges and issues that can affect the usability of such systems: in- creased task complexity, user’s lack of or limited task knowledge, and longer system turns. In typical information access dialogue systems, the task is relatively simple: get the information from the user and return the query results with minimal complexity added by confirmation dia- logues. Moreover, in most cases, users have knowledge about the task. However, in complex domains things are different. Take for example tutoring. A tutoring dialogue system has to discuss concepts, laws and relationships and to engage in complex subdialogues to correct user misconcep- tions. In addition, it is very likely that users of such systems are not familiar or are only partially famil- iar with the tutoring topic. The length of system turns can also be affected as these systems need to make explicit the connections between parts of the underlying task. Thus, interacting with such systems can be char- acterized by an increased user cognitive load asso- ciated with listening to often lengthy system turns and the need to integrate the current information to the discussion overall (Oviatt et al., 2004). We hypothesize that one way to reduce the user’s cognitive load is to make explicit two pieces of information: the purpose of the current system turn, and how the system turn relates to the overall discussion. This information is implicitly encoded in the intentional structure of a discourse as pro- posed in the Grosz & Sidner theory of discourse (Grosz and Sidner, 1986). Consequently, in this paper we propose using a graphical representation of the discourse structure as a way of improving the performance of com- plex-domain dialogue systems (note that graphical output is required). We call it the Navigation Map (NM). The NM is a dynamic representation of the discourse segment …

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