IEEE Intelligent Systems
Towards developing general models of usability with PARADISE
Natural Language Engineering
Statistical acquisition of content selection rules for natural language generation
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Trainable sentence planning for complex information presentation in spoken dialog systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Learning more effective dialogue strategies using limited dialogue move features
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Hybrid reinforcement/supervised learning of dialogue policies from fixed data sets
Computational Linguistics
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
Individual and domain adaptation in sentence planning for dialogue
Journal of Artificial Intelligence Research
Generating and evaluating evaluative arguments
Artificial Intelligence
Learning human multimodal dialogue strategies
Natural Language Engineering
Learning to adapt to unknown users: referring expression generation in spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Optimising information presentation for spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning to adapt to unknown users: referring expression generation in spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Optimising information presentation for spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Natural language generation as planning under uncertainty for spoken dialogue systems
Empirical methods in natural language generation
Adaptive referring expression generation in spoken dialogue systems: evaluation with real users
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Spatially-aware dialogue control using hierarchical reinforcement learning
ACM Transactions on Speech and Language Processing (TSLP)
Bootstrapping semantic parsers from conversations
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Talkin' bout a revolution (statistically speaking)
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Adaptive information presentation for spoken dialogue systems: evaluation with human subjects
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
Advances in Human-Computer Interaction
Comparing HMMs and Bayesian networks for surface realisation
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Probabilistic dialogue models with prior domain knowledge
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Using agents in virtual environments to assist controllers to manage multiple assets
CAVE'12 Proceedings of the First international conference on Cognitive Agents for Virtual Environments
A domain-independent statistical methodology for dialog management in spoken dialog systems
Computer Speech and Language
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This paper argues that the problems of dialogue management (DM) and Natural Language Generation (NLG) in dialogue systems are closely related and can be fruitfully treated statistically, in a joint optimisation framework such as that provided by Reinforcement Learning (RL). We first review recent results and methods in automatic learning of dialogue management strategies for spoken and multimodal dialogue systems, and then show how these techniques can also be used for the related problem of Natural Language Generation. This approach promises a number of theoretical and practical benefits such as fine-grained adaptation, generalisation, and automatic (global) optimisation, and we compare it to related work in statistical/trainable NLG. A demonstration of the proposed approach is then developed, showing combined DM and NLG policy learning for adaptive information presentation decisions. A joint DM and NLG policy learned in the framework shows a statistically significant 27% relative increase in reward over a baseline policy, which is learned in the same way only without the joint optimisation. We thereby show that that NLG problems can be approached statistically, in combination with dialogue management decisions, and we show how to jointly optimise NLG and DM using Reinforcement Learning.