Phrase-Based Statistical Machine Translation
KI '02 Proceedings of the 25th Annual German Conference on AI: Advances in Artificial Intelligence
A systematic comparison of various statistical alignment models
Computational Linguistics
Parsing inside-out
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Synchronous binarization for machine translation
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Design of the moses decoder for statistical machine translation
SETQA-NLP '08 Software Engineering, Testing, and Quality Assurance for Natural Language Processing
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
Why generative phrase models underperform surface heuristics
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Constraining the phrase-based, joint probability statistical translation model
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Binarization of synchronous context-free grammars
Computational Linguistics
Learning probabilistic synchronous CFGs for phrase-based translation
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Translation model generalization using probability averaging for machine translation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Learning hierarchical translation structure with linguistic annotations
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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The conditional phrase translation probabilities constitute the principal components of phrase-based machine translation systems. These probabilities are estimated using a heuristic method that does not seem to optimize any reasonable objective function of the word-aligned, parallel training corpus. Earlier efforts on devising a better understood estimator either do not scale to reasonably sized training data, or lead to deteriorating performance. In this paper we explore a new approach based on three ingredients (1) A generative model with a prior over latent segmentations derived from Inversion Transduction Grammar (ITG), (2) A phrase table containing all phrase pairs without length limit, and (3) Smoothing as learning objective using a novel Maximum-A-Posteriori version of Deleted Estimation working with Expectation-Maximization. Where others conclude that latent segmentations lead to overfitting and deteriorating performance, we show here that these three ingredients give performance equivalent to the heuristic method on reasonably sized training data.