Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A systematic comparison of various statistical alignment models
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
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
Accelerated training of conditional random fields with stochastic gradient methods
ICML '06 Proceedings of the 23rd international conference on Machine learning
An end-to-end discriminative approach to machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A block bigram prediction model for statistical machine translation
ACM Transactions on Speech and Language Processing (TSLP)
The complexity of phrase alignment problems
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Probabilistic inference for machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Sampling alignment structure under a Bayesian translation model
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Why generative phrase models underperform surface heuristics
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Machine translation evaluation versus quality estimation
Machine Translation
Discriminative modeling of extraction sets for machine translation
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
From n-gram-based to CRF-based translation models
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
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We present a new phrase-based conditional exponential family translation model for statistical machine translation. The model operates on a feature representation in which sentence level translations are represented by enumerating all the known phrase level translations that occur inside them. This makes the model a good match with the commonly used phrase extraction heuristics. The model's predictions are properly normalized probabilities. In addition, the model automatically takes into account information provided by phrase overlaps, and does not suffer from reference translation reachability problems. We have implemented an open source translation system Sinuhe based on the proposed translation model. Our experiments on Europarl and GigaFrEn corpora demonstrate that finding the unique MAP parameters for the model on large scale data is feasible with simple stochastic gradient methods. Sinuhe is fast and memory efficient, and the BLEU scores obtained by it are only slightly inferior to those of Moses.