Forest-based statistical sentence generation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Trainable methods for surface natural language generation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Exploiting a probabilistic hierarchical model for generation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Robust PCFG-based generation using automatically acquired LFG approximations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Dependency parsing based on dynamic local optimization
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Dependency-based n-gram models for general purpose sentence realisation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Stochastic realisation ranking for a free word order language
ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation
Probabilistic models for disambiguation of an HPSG-based chart generator
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Broad coverage multilingual deep sentence generation with a stochastic multi-level realizer
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Generating non-projective word order in statistical linearization
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Partial-tree linearization: generalized word ordering for text synthesis
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper describes log-linear models for a general-purpose sentence realizer based on dependency structures. Unlike traditional realizers using grammar rules, our method realizes sentences by linearizing dependency relations directly in two steps. First, the relative order between head and each dependent is determined by their dependency relation. Then the best linearizations compatible with the relative order are selected by log-linear models. The log-linear models incorporate three types of feature functions, including dependency relations, surface words and headwords. Our approach to sentence realization provides simplicity, efficiency and competitive accuracy. Trained on 8,975 dependency structures of a Chinese Dependency Treebank, the realizer achieves a BLEU score of 0.8874.