User evaluation of the MASK kiosk
Speech Communication
Automatic optimization of dialogue management
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance
User Modeling and User-Adapted Interaction
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Fast methods for kernel-based text analysis
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Spoken dialogue management using probabilistic reasoning
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Implementing clarification dialogues in open domain question answering
Natural Language Engineering
User Modeling and User-Adapted Interaction
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
Dialogue management in the Mercury flight reservation system
ConversationalSys '00 Proceedings of the ANLP-NAACL 2000 Workshop on Conversational Systems
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
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We propose an efficient technique of dialogue management for an information navigation system based on a document knowledge base. The system can use ASR N-best hypotheses and contextual information to perform robustly for fragmental speech input and erroneous output of automatic speech recognition (ASR). It also has several choices in generating responses or confirmations. We formulate the optimization of these choices based on a Bayes risk criterion, which is defined based on a reward for correct information presentation and a penalty for redundant turns. The parameters for the dialogue management we propose can be adaptively tuned by online learning. We evaluated this strategy with our spoken dialogue system called ''Dialogue Navigator for Kyoto City'', which generates responses based on the document retrieval and also has question-answering capability. The effectiveness of the proposed framework was demonstrated by the increased success rate of dialogue and the reduced number of turns for information access through an experiment with a large number of utterances by real users.