Selective Sampling Using the Query by Committee Algorithm
Machine Learning
Active Learning for Natural Language Parsing and Information Extraction
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
A systematic comparison of various statistical alignment models
Computational Linguistics
Generation that exploits corpus-based statistical knowledge
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Exploiting a probabilistic hierarchical model for generation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Active learning for statistical natural language parsing
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
An empirical study of active learning with support vector machines for Japanese word segmentation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Instance-based natural language generation
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Factored language models and generalized parallel backoff
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Empirically-based control of natural language generation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Natural Language Engineering
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
Agenda-based user simulation for bootstrapping a POMDP dialogue system
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management
Computer Speech and Language
Probabilistic models for disambiguation of an HPSG-based chart generator
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Individuality and alignment in generated dialogues
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
Bayesian update of dialogue state: A POMDP framework for spoken dialogue systems
Computer Speech and Language
Bucking the trend: large-scale cost-focused active learning for statistical machine translation
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Bucking the trend: large-scale cost-focused active learning for statistical machine translation
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Controlling user perceptions of linguistic style: Trainable generation of personality traits
Computational Linguistics
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
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
Towards a surface realization-oriented corpus annotation
INLG '12 Proceedings of the Seventh International Natural Language Generation Conference
Optimising incremental generation for spoken dialogue systems: reducing the need for fillers
INLG '12 Proceedings of the Seventh International Natural Language Generation Conference
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Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to inform the generation decision process. Both approaches rely on the existence of a handcrafted generator, which limits their scalability to new domains. This paper presents Bagel, a statistical language generator which uses dynamic Bayesian networks to learn from semantically-aligned data produced by 42 untrained annotators. A human evaluation shows that Bagel can generate natural and informative utterances from unseen inputs in the information presentation domain. Additionally, generation performance on sparse datasets is improved significantly by using certainty-based active learning, yielding ratings close to the human gold standard with a fraction of the data.