CAREER: Prevention, Detection and Repair of Miscommunication in Spoken Natural Language Dialog Processing Systems

Ronnie W. Smith

East Carolina University
Department of Mathematics
Greenville, NC 27858


phone: (919) 328-1906
fax: (919) 328-6414



Speech and Natural Language Understanding


Spoken Natural Language Dialog, Miscommunication,


Recent improvements in speech recognition technology have made spoken natural language interfaces a viable means of human-computer interaction. To fully exploit this mode of communication, the speech recognition capabilities must be integrated within a dialog processing mechanism. An important unresolved issue in spoken natural language dialog processing is the handling of miscommunication. By studying previously recorded human-human and human-computer dialogs, this project will investigate strategies for reducing miscommunication in natural language dialog via the following steps:


R.W. Smith, D.R. Hipp, and A.W. Biermann, "An Architecture for Voice Dialog Systems Based on Prolog-Style Theorem Proving," Computational Linguistics, vol. 21, no. 3, pages 281-320, September 1995.

R.W. Smith and D.R. Hipp, Spoken Natural Language Dialog Systems: A Practical Approach, Oxford University Press, 1994.

R.W. Smith, "Spoken Variable Initiative Dialog: An Adaptable Interface," IEEE Expert, vol. 9, no. 1, pages 45-50, February 1994.

R.W. Smith, D.R. Hipp, and A.W. Biermann, "A Dialog Control Algorithm and Its Performance," Proceedings of the 3rd Conference on Applied Natural Language Processing, pages 9-16, April, 1992.

R.W. Smith, "Integration of Domain Problem Solving with Natural Language Dialog: The Missing Axiom Theory," Proceedings of Applications of AI X: Knowledge-Based Systems, pages 270-278, April, 1992.

R.W. Smith and D.R. Hipp, "Using Expectation to Enable Spoken Variable Initiative Dialog," in Proceedings of the 1992 Symposium on Applied Computing, pages 123-130, March, 1992.


My study of computational modeling of natural language dialog has focused on issues concerning voice interfaces, real-time interaction, and integrated modeling of the following behaviors: (1) collaborative problem solving, (2) subdialog completion and movement, (3) contextual interpretation, (4) user-dependent response generation, and (5) mixed-initiative interaction. This wholistic modeling of natural language dialog requires an awareness of work on various subproblems in dialog processing including quantification, presuppositions, ellipsis, anaphoric reference, user modeling, expectation modeling, plan recognition, and miscommunication handling.

An important methodlogy for validation of the computational model is system construction and formal experimentation. The goal of empirically validating the model necessitates an awareness of computational constraints and robust error handling techniques as well as familiarity with past experimental studies on discourse behavior (usually of the human-human or simulated human-computer variety). Empirical study is beneficial in acquiring knowledge about how human linguistic behavior during interaction with a computer may differ from what would occur if the interaction was with another human.


J.F. Allen, L.K. Schubert, G. Ferguson, P. Heeman, C.H. Hwang, T. Kato, M. Light, N. Martin, B. Miller, M. Poesio, and D.R. Traum, "The TRAINS Project: A Case Study in Building a Conversational Planning Agent." Journal of Experimental and Theoretical Artificial Intelligence. vol. 7, pages 7-48, January, 1995.

V.W. Zue, "Toward Systems that Understand Spoken Language," IEEE Expert, vol. 9, no. 1, pages 51-59, February 1994.

S. Carberry, Plan Recognition in Natural Language Dialogue, MIT Press, Cambridge, Mass., 1990.

S.R. Young, A.G. Hauptmann, W.H. Ward, E.T. Smith, and P. Werner, "High Level Knowledge Sources in Usable Speech Recognition Systems," Communications of the ACM, vol. 32, no. 2, pages 183-194, February 1989.

T.W. Finin, "GUMS: A General User Modeling Shell," User Models in Dialog Systems, A. Kobsa and W. Wahlster, editors, Springer-Verlag, New York, pages 411-430, 1989.

R. Wilensky, D.N. Chin, M. Luria, J. Martin, J. Mayfield, and D. Wu, "The Berkeley UNIX Consultant Project", Computational Linguistics, vol. 14, no. 4, pages 35-84, 1988.

B.J. Grosz and C.L. Sidner, "Attentions, Intentions, and the Structure of Discourse", Computational Linguistics, vol. 12, no. 3, pages 175-204, 1986.


Adapative Human Interfaces Intelligent Interactive Systems for Persons with Disabilities.