Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Generation that exploits corpus-based statistical knowledge
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Immediate-head parsing for language models
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Learning as search optimization: approximate large margin methods for structured prediction
ICML '05 Proceedings of the 22nd international conference on Machine learning
Discriminative Reranking for Natural Language Parsing
Computational Linguistics
AI Magazine - Special issue on achieving human-level AI through integrated systems and research
Acquiring correct knowledge for natural language generation
Journal of Artificial Intelligence Research
Evaluating coverage for large symbolic NLG grammars
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Building effective question answering characters
SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
Practical grammar-based NLG from examples
INLG '08 Proceedings of the Fifth International Natural Language Generation Conference
Practical grammar-based NLG from examples
INLG '08 Proceedings of the Fifth International Natural Language Generation Conference
Generating expository dialogue from monologue: motivation, corpus and preliminary rules
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Harvesting re-usable high-level rules for expository dialogue generation
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
FamCHAI: an adaptive calendar dialogue system
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
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We present a development pipeline and associated algorithms designed to make grammarbased generation easier to deploy in implemented dialogue systems. Our approach realizes a practical trade-off between the capabilities of a system's generation component and the authoring and maintenance burdens imposed on the generation content author for a deployed system. To evaluate our approach, we performed a human rating study with system builders who work on a common largescale spoken dialogue system. Our results demonstrate the viability of our approach and illustrate authoring/performance trade-offs between hand-authored text, our grammar-based approach, and a competing shallow statistical NLG technique.