Making large-scale support vector machine learning practical
Advances in kernel methods
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Estimators for stochastic "Unification-Based" grammars
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Feature selection for a rich HPSG grammar using decision trees
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Probabilistic models for disambiguation of an HPSG-based chart generator
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
High efficiency realization for a wide-coverage unification grammar
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Human evaluation of a German surface realisation ranker
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Feature selection for fluency ranking
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
Human evaluation of a german surface realisation ranker
Empirical methods in natural language generation
Underspecifying and predicting voice for surface realisation ranking
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Reversible stochastic attribute-value grammars
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Deep open-source machine translation
Machine Translation
Lfg generation by grammar specialization
Computational Linguistics
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In this paper we describe and evaluate several statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input semantics. Three models (and several variants) are trained and tested: an n-gram language model, a discriminative maximum entropy model using structural information (and incorporating the language model as a separate feature), and finally an SVM ranker trained on the same feature set. The resulting hybrid tactical generator is part of a larger, semantic transfer MT system.