Generating descriptions that exploit a user's domain knowledge
Current research in natural language generation
Towards developing general models of usability with PARADISE
Natural Language Engineering
Trainable sentence planning for complex information presentation in spoken dialog systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Data-driven user simulation for automated evaluation of spoken dialog systems
Computer Speech and Language
Mixture model POMDPs for efficient handling of uncertainty in dialogue management
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Natural language generation as planning under uncertainty for spoken dialogue systems
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
What game theory can do for NLG: the case of vague language
ENLG '09 Proceedings of the 12th European Workshop on Natural Language Generation
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
Computer Speech and Language
Training and evaluation of the HIS POMDP dialogue system in noise
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
SIGDIAL '09 Proceedings of the SIGDIAL 2009 Conference: The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue
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
Talkin' bout a revolution (statistically speaking)
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
The GRUVE challenge: generating routes under uncertainty in virtual environments
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
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We invite the research community to consider challenges for NLG which arise from uncertainty. NLG systems should be able to adapt to their audience and the generation environment in general, but often the important features for adaptation are not known precisely. We explore generation challenges which could employ simulated environments to study NLG which is adaptive under uncertainty, and suggest possible metrics for such tasks. It would be particularly interesting to explore how different planning approaches to NLG perform in challenges involving uncertainty in the generation environment.