Conversation as Action Under Uncertainty
Stanford, CA 94305
Redmond, Washington 98052
Author email: firstname.lastname@example.org, email@example.com
Conversations abound with uncertainties of various kinds. Treating conversation as inference and decision making under uncertainty, we propose a task independent, multimodal architecture for supporting robust continuous spoken dialog called Quartet. We introduce four interdependent levels of analysis, and describe representations, inference procedures, and decision strategies for managing uncertainties within and between the levels. We highlight the approach by reviewing interactions between a user and two spoken dialog systems developed using the Quartet architecture: Presenter, a prototype system for navigating Microsoft PowerPoint presentations, and the Bayesian Receptionist, a prototype system for dealing with tasks typically handled by front desk receptionists at the Microsoft corporate campus.
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Keywords: Bayesian user modeling, common ground, joint activity, conversational systems, dialog systems, computational linguistics.
In: Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence, Stanford, CA, June 2000. San Francisco: Morgan Kaufmann.
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