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User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance

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Abstract

We address the issue of appropriate user modeling to generate cooperative responses to users in spoken dialogue systems. Unlike previous studies that have focused on a user’s knowledge, we propose more generalized modeling. We specifically set up three dimensions for user models: the skill level in use of the system, the knowledge level about the target domain, and the degree of urgency. Moreover, the models are automatically derived by decision tree learning using actual dialogue data collected by the system. We obtained reasonable accuracy in classification for all dimensions. Dialogue strategies based on user modeling were implemented on the Kyoto City Bus Information System that was developed at our laboratory. Experimental evaluations revealed that the cooperative responses adapted to each subject type served as good guides for novices without increasing the duration dialogue lasted for skilled users.

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References

  • Bernsen N.O. (2003). On-line User Modelling in a Mobile Spoken Dialogue System. In: Proceedings of the European Conference on Speech Communication & Technology (EUROSPEECH), Geneva, Switzerland, pp. 737–740

  • Chu-Carroll J. (2000). MIMIC: An Adaptive Mixed Initiative Spoken Dialogue System for Information Queries. In: Proceedings of the 6th Conference on Applied Natural Language Processing, Seättle, WA, pp. 97–104

  • Eckert W., Levin E., Pieraccini R. (1997). User Modeling For Spoken Dialogue System Evaluation. In: Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding. Santa Barbara CA, pp. 80–87

  • Elzer S., Chu-Carroll J., Carberry S. (1994). Recognizing and Utilizing User Preferences in Collaborative Consultation Dialogues. In: Proceedings of the 4th International Conference on User Modeling. Cape Cod MA, pp. 19–24

  • Hazen T.J., Burianek T., Polifroni J., Seneff S. (2000). Integrating Recognition Confidence Scoring with Language Understanding and Dialogue Modeling. In: Proceedings International Conference on Spoken Language Processing (ICSLP). Beijing China, pp. 1042–1045

  • R. Kass T. Finin (1988) ArticleTitleModeling the User in Natural Language Systems Computational Linguistics. 14 IssueID3 5–22

    Google Scholar 

  • Komatani K., Kawahara T. (2000). Flexible mixed-initiative dialogue management using concept-level confidence measures of speech recognizer output. In: Proceedings International Conference on Computational Linguistics (COLING). Saarbrucken, Germany, pp. 467–473

  • Komatani K., Ueno S., Kawahara T., Okuno H.G. (2003). Flexible Guidance Generation using User Model in Spoken Dialogue Systems. In: Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL-03). Sapporo, Japan, pp. 256–263

  • Lamel L., Rosset S., Gauvain J.-L., Bennacef S. (1999). The LIMSI ARISE System for Train Travel Information. In: IEEE International Conference Acoust., Speech & Signal Processing (ICASSP). Phoenix, AZ, pp. 501–504

  • Litman D.J., Pan S. (2000). Predicting and Adapting to Poor Speech Recognition in a Spoken Dialogue System. In: Proceedings of the 17th National Conference on Artificial Intelligence (AAAI2000). Austin, TX, pp. 722–728

  • Over P. (1999). TREC-7 Interactive Track Report. In: Proceedings of the 7th Text REtrieval Conference (TREC7). Gaithersburg, MD, pp. 65–72

  • C.L. Paris (1988) ArticleTitleTailoring Object Descriptions to a User’s Level of Expertise Computational Linguistics. 14 IssueID3 64–78

    Google Scholar 

  • Quinlan J.R. (1993). C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann. http://www.rulequest.com/see5-info.html

  • Sadek D. (1999). Design Considerations on Dialogue Systems: From Theory to Technology -The Case of Artimis-. In: Proceedings ESCA Workshop on Interactive Dialogue in Multi-Modal Systems, Klosler lrsee, Germany, pp. 173–187

  • Sturm J., den Os E., Boves L. (1999). Issues in Spoken Dialogue Systems: Experiences with the Dutch ARISE System. In: Proceedings of the ESCA Workshop on Interactive Dialogue in Multi-Modal Systems, Klosler, lrsee, Germany, pp. 1–4

  • van Beek P. (1987). A Model For Generating Better Explanations. In: Proceedings of the 25th Annual Meeting of the Association for Computational Linguistics (ACL-87), Stanford, CA, pp. 215–220

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Komatani, K., Ueno, S., Kawahara, T. et al. User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance. User Model User-Adap Inter 15, 169–183 (2005). https://doi.org/10.1007/s11257-004-5659-0

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