Modeling the user in natural language systems
Computational Linguistics - Special issue on user modeling
Tailoring object descriptions to a user's level of expertise
Computational Linguistics - Special issue on user modeling
C4.5: programs for machine learning
C4.5: programs for machine learning
Predicting and Adapting to Poor Speech Recognition in a Spoken Dialogue System
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
MIMIC: an adaptive mixed initiative spoken dialogue system for information queries
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A model for generating better explanations
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Flexible guidance generation using user model in spoken dialogue systems
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The LIMSI ARISE system for train travel information
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01
Interaction Reproducing Model: A Model for Giving Supports Appropriate to User State
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A Model of Temporally Changing User Behaviors in a Deployed Spoken Dialogue System
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Smart cooking support system based on interaction reproducing model
CEA '09 Proceedings of the ACM multimedia 2009 workshop on Multimedia for cooking and eating activities
SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Learning adaptive referring expression generation policies for spoken dialogue systems
Empirical methods in natural language generation
Modeling spoken decision making dialogue and optimization of its dialogue strategy
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Modeling spoken decision support dialogue and optimization of its dialogue strategy
ACM Transactions on Speech and Language Processing (TSLP)
Achieving rapport with turn-by-turn, user-responsive emotional coloring
Speech Communication
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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.