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
CONTACT INFORMATION
email: rws@math1.math.ecu.edu
phone: (919) 328-1906
fax: (919) 328-6414
WWW PAGE
http://www.cs.ecu.edu/faculty/smith/www/smith.html
PROGRAM AREA
Speech and Natural Language Understanding
KEYWORDS
Spoken Natural Language Dialog, Miscommunication,
PROJECT SUMMARY
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:
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Categorizing initiative-dependent features of human-computer
task-oriented dialogs as users evolve from novice to expert.
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Developing a context-based model for selective verification of user inputs
whose meaning is in question.
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Developing strategies for permitting either computer or user-initiated
subdialogs for resolving miscommunications detected at some later point in the
dialog.
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Implementing these theories and evaluating their performance under both
simulated and experimental conditions.
PROJECT REFERENCES
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.
AREA BACKGROUND
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.
AREA REFERENCES
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.
RELATED PROGRAM AREAS
Adapative Human Interfaces
Intelligent Interactive Systems for Persons with Disabilities.
POTENTIAL RELATED PROJECTS
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Port the dialog model to other domains such as advisory dialogs or to other
environments such as telephone interactions.
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Achieve total integration of the model with a speech recognition system to
enhance robustness and efficiency.
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Conduct large-scale user testing of the dialog model via a system that assists
in completing a complex real-world task (i.e., a task requiring a vocabulary of
500 words or more).