Conversational Architectures Project
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Here is a sample paper on the project:
A Computational Architecture for Conversation
Eric Horvitz
Microsoft Research
Redmond, Washington 98052
Tim Paek
Stanford University
Stanford, CA 94305
Author email: horvitz@microsoft.com, paek@psych.stanford.edu
Abstract:
We describe representation, inference strategies, and control
procedures employed in an automated conversation system named the
Bayesian Receptionist. The prototype is focused on the domain of
dialog about goals typically handled by receptionists at the front
desks of buildings on the Microsoft corporate campus. The system
employs a set of Bayesian user models to interpret the goals of
speakers given evidence gleaned from a natural language parse of their
utterances. Beyond linguistic features, the domain models take into
consideration contextual evidence, including visual findings. We
discuss key principles of conversational actions under uncertainty and
the overall architecture of the system, highlighting the use of a
hierarchy of Bayesian models at different levels of detail, the use of
value of information to control question asking, and application of
expected utility to control progression and backtracking in
conversation.
Click here to access postscript or pdf file.
Keywords: Bayesian user modeling, common ground, joint activity, conversational systems, dialog systems, computational linguistics.
In: Proceedings of the Seventh International Conference on User Modeling, Banff, Canada, June 1999. New York: Springer Wien, pp. 201-210.
Related Papers
T. Paek and E. Horvitz, Uncertainty, Utility, and Misunderstanding: A
Decision-Theoretic Perspective on Grounding in Conversational Systems,
AAAI Fall Symposium on Psychological Models of Communication in
Collaborative Systems, Cape Cod, MA. November 5-7, 1999.