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Interactive question answering and constraint relaxation in spoken dialogue systems

Published online by Cambridge University Press:  01 January 2009

S. VARGES
Affiliation:
Department of Information and Communication Technology, University of Trento, 38050 Povo di Trento, Italy e-mail: [email protected]
F. WENG
Affiliation:
Bosch Research and Technology Center, 4009 Miranda Ave., Palo Alto, CA 94304, USA e-mail: [email protected]
H. PON-BARRY
Affiliation:
School of Engineering and Applied Sciences, Harvard University, 33 Oxford St., Cambridge, MA 02138, USA e-mail: [email protected]

Abstract

We explore the relationship between question answering and constraint relaxation in spoken dialogue systems and develop dialogue strategies for selecting and presenting information succinctly. In particular, we describe methods for dealing with the results of database queries in information-seeking dialogues. Our goal is to structure the dialogue in such a way that the user is neither overwhelmed with information nor left uncertain as to how to refine the query further. We present two sets of evaluation results for a restaurant selection task: one is a system performance evaluation experiment involving twenty subjects, the other is an experimental evaluation of the use of suggestions involving sixteen subjects.

Type
Papers
Copyright
Copyright © Cambridge University Press 2008

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References

Bratt, E. O., Schultz, K., Peters, S., Chen, T., and Pon-Barry, H. 2005. Empirical foundations for intelligent coaching systems. In Proceedings of The Interservice/Industry Training, Simulation and Education Conference (I/ITSEC) '05, Orlando, FL.Google Scholar
Brockmann, C., Isard, A., Oberlander, J., and White, M. 2005. Modelling alignment for affective dialogue. In Proceedings of the UM'05 Workshop on Adapting the Interaction Style to Affective Factors, Edinburgh, UK.Google Scholar
Cheng, H., Bratt, H., Mishra, R., Shriberg, E., Upson, S., Chen, J., Weng, F., Peters, S., Cavedon, Y., and Niekrasz, J. 2004. A Wizard-of-Oz framework for collecting spoken human-computer dialogs. In Proceedings of Interspeech/ICSLP '04, Jeju Island, Korea.Google Scholar
Chung, G. 2004. Developing a flexible spoken dialog system using simulation. In Proceedings of ACL '04, Barcelona, Spain.CrossRefGoogle Scholar
Dale, R., and Reiter, E. 1995. Computational interpretations of the Gricean maxims in the generation of referring expressions. Cognitive Science 19: 233263.CrossRefGoogle Scholar
Demberg, V., and Moore, J. 2006. Information presentation in spoken dialogue systems. In Proceedings of the European Chapter of the ACL (EACL) '06, Trento, Italy.Google Scholar
Frank, A., Krieger, H.-U., Xu, F., Uszkoreit, H., Crysmann, B., Jörg, B., and Schäfer, U. 2005. Question answering from structured knowledge sources. Journal of Applied Logic 5 (2), 2048; Special Issue on Questions and Answers: Theoretical and Applied Perspectives, Amsterdam.Google Scholar
Gennari, J. H., Musen, M. A., Fergerson, R. W., Grosso, W. E., Crubézy, M., Eriksson, H., Noy, N. F., and Tu, S. W. 2002. The evolution of protégé: An environment for knowledge-based systems development. Technical Report, Stanford University.CrossRefGoogle Scholar
Kaplan, J. 1983. Coorperative responses from a portable natural language database query language. In Brady, Michael and Berwick, Robert C. (eds.), Computational Models of Discourse, pp. 167208. Cambridge, MA: MIT Press.Google Scholar
Kruijff-Korbayova, I., Karagjosova, E., and Larsson, S. 2002. Enhancing collaboration with conditional responses in information-seeking dialogues. In Proceedings of 6th Workshop on the Semantics and Pragmatics of Dialogue (EDILOG '02), Edinburgh, UK.CrossRefGoogle Scholar
Kruschwitz, U., and Al-Bakour, H. 2005. Users want more sophisticated search assistants: Results of a task-based evaluation. Journal of the Americal Society for Information Science and Technology 56 (13): 13771393.CrossRefGoogle Scholar
Langkilde, I. 2000. Forest-based statistical sentence generation. In Proceedings of the North American Chapter of the ACL (NAACL) '00, Seattle, WA.Google Scholar
Langkilde, I., and Knight, K. 1998. Generation that exploits corpus-based statistical knowledge. In Proceedings of COLING/ACL-98, pp. 704–710. Montreal, Canada.CrossRefGoogle Scholar
Larsson, S., and Traum, D. 2000. Information state and dialogue management in the TRINDI dialogue move engine toolkit. Natural Language Engineering 6 (3–4): 323340.CrossRefGoogle Scholar
Lemon, O., Gruenstein, A., Battle, A., and Peters, S. 2002. Multi-tasking and collaborative activities in dialogue systems. In Proceedings of 3rd SIGdial Workshop on Discourse and Dialogue, Philadelphia, PA.CrossRefGoogle Scholar
Mirkovic, D., and Cavedon, L. 2005. Practical plug-and-play dialogue management. In Proceedings of the 6th Meeting of the Pacific Association for Computational Linguistics (PACLING), Tokyo, Japan.Google Scholar
Pellom, B., Ward, W., and Pradhan, S. 2000. The CU Communicator: An architecture for dialogue systems. In Proceedings of Interspeech/ICSLP '00, Beijing, China.CrossRefGoogle Scholar
Pon-Barry, H., Weng, F., and Varges, S. 2006. Evaluation of content presentation strategies for an in-car spoken dialogue system. In Proceedings of Interspeech/ICSLP '06, Pittsburgh, PA.CrossRefGoogle Scholar
Purver, M., Ratiu, F., and Cavedon, L. 2006. Robust interpretation in dialogue by combining confidence scores with contextual features. In Proceedings of Interspeech/ICSLP '06, Pittsburgh, PA.CrossRefGoogle Scholar
Qu, Y., and Green, N. 2002. A constraint-based approach for cooperative information-seeking dialogue. In Proceedings of the International Workshop on Natural Language Generation (INLG '02), New York.Google Scholar
Reiter, E., and Dale, R. 2000. Building Applied Natural Language Generation Systems. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Rieser, V., and Lemon, O. 2007. Learning dialogue strategies for interactive database search. In Proceedings of Interspeech, Antwerp, Belgium.CrossRefGoogle Scholar
Traum, D. 1994. A Computational Theory of Grounding in Natural Language Conversation. Ph.D. thesis, Computer Science Department, University of Rochester.Google Scholar
Varges, S. 2004. Overgenerating referring expressions involving relations. In Proceedings of the Third International Conference on Natural Language Generation (INLG '04), Brockenhurst, UK.CrossRefGoogle Scholar
Varges, S. 2005. Chart generation using production systems (short paper). In Proceedings of 10th European Workshop on Natural Language Generation, Aberdeen, Scotland.Google Scholar
Varges, S., and Mellish, C. 2001. Instance-based natural language generation. In Proceedings of the 2nd Meeting of the ACL (NAACL '01), Carnegie Mellon University, Pittsburgh, PA.CrossRefGoogle Scholar
Varges, S., and Purver, M. 2006. Robust language analysis and generation for spoken dialogue systems (short paper). In Proceedings of the ECAI 06 Workshop on the Development and Evaluation of Robust Spoken Dialogue Systems, Riva del Garda, Italy.Google Scholar
Walker, M. A., Whittaker, S. J., Stent, A., Maloor, P., Moore, J. D., Johnston, M., and Vasireddy, G. 2004. Generation and evaluation of user tailored responses in multimodal dialogue. Cognitive Science 28: 811840.CrossRefGoogle Scholar
Weng, F., Cavedon, L., Raghunathan, B., Mirkovic, D., Bei, B., Pon-Barry, H., Bratt, H., Cheng, H., Schmidt, H., Mishra, R., Lathrop, B., Zhang, Q., Scheideck, T., Xu, K., Hand-Bender, T., Peters, S., Shriberg, L., and Bergmann, C. 2005. A flexible conversational dialog system for MP3 player. In demo session of HLT-EMNLP 2005, Vancouver, Canada.CrossRefGoogle Scholar
Weng, F., Cavedon, L., Raghunathan, B., Mirkovic, D., Cheng, H., Schmidt, H., Bratt, H., Mishra, R., Peters, S., Upson, S., Shriberg, E., Bergmann, C., and Zhao, L. 2004a. A conversational dialogue system for cognitively overloaded users. In Proceedings of Interspeech/ICSLP '04, Jeju Island, Korea.CrossRefGoogle Scholar
Weng, F., Cavedon, L., Raghunathan, B., Mirkovic, D., Cheng, H., Schmidt, H., Bratt, H., Mishra, R., Peters, S., Zhao, L., Upson, S., Shriberg, E., and Bergmann, C. 2004b. Developing a conversational dialogue system for cognitively overloaded users. In Proceedings of the International Congress on Intelligent Transportation Systems, San Francisco, CA.CrossRefGoogle Scholar
Weng, F., Jin, N., Meng, J., and Zhu, Y. 2001. A novel probabilistic model for link unification grammar. In Proceedings of the 7th International Workshop on Parsing Technologies (ACL/SIGPARSE), Beijing, China.Google Scholar
Weng, F., Yan, B., Feng, Z., Ratiu, F., Raya, M., Lathrop, B., Lien, A., Mishra, R., Varges, S., Lin, F., Purver, M., Meng, Y., Bratt, H., Scheideck, T., Zhang, Z., Raghunathan, B., and Peters, S. 2007. CHAT to your destination. In Proceedings of 8th SIGdial Workshop on Discourse and Dialogue, Antwerp, Belgium.Google Scholar
Woods, W. A., Kaplan, R. M., and Nash-Webber, B. L. 1972. The Lunar Sciences Natural Language Information System: Final Report. BBN Report No. 2378, Bolt Beranek and Newman Inc., Cambridge, MA. (Available from NTIS as N72-28984.)Google Scholar
Zhang, Q., and Weng, F. 2005. Exploring features for identifying edited regions in disfluent sentences. In Proceedings of the 9th International Workshop on Parsing Technologies (IWPT-05), Vancouver, CA.CrossRefGoogle Scholar
Zhang, Q., Weng, F., and Feng, Z. 2006. A progressive feature selection algorithm for ultra large feature spaces and its application to edit region identification. In Proceedings of ACL '06, Sydney, Australia.CrossRefGoogle Scholar