A statistical approach to machine translation
Computational Linguistics
Finite-State Speech-to-Speech Translation
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Learning dependency translation models as collections of finite-state head transducers
Computational Linguistics - Special issue on finite-state methods in NLP
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Decoding complexity in word-replacement translation models
Computational Linguistics
Decoding algorithm in statistical machine translation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Word re-ordering and DP-based search in statistical machine translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Fast decoding and optimal decoding for machine translation
ACL '01 Proceedings of the 39th 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
The Candide system for machine translation
HLT '94 Proceedings of the workshop on Human Language Technology
An efficient A* search algorithm for statistical machine translation
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Cross-lingual C*ST*RD: English access to Hindi information
ACM Transactions on Asian Language Information Processing (TALIP)
Learning finite-state models for machine translation
Machine Learning
Word sense disambiguation vs. statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
An algorithmic framework for the decoding problem in statistical machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
OCR post-processing for low density languages
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Statistical machine translation
ACM Computing Surveys (CSUR)
MSD Recombination for Statistical Machine Translation into Highly-Inflected Languages
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Generalized graphical abstractions for statistical machine translation
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Assessing phrase-based translation models with oracle decoding
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Panning for EBMT gold, or "Remembering not to forget"
Machine Translation
Czech-English phrase-based machine translation
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Aligning turkish and english parallel texts for statistical machine translation
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
A phrase-based context-dependent joint probability model for named entity translation
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Document-wide decoding for phrase-based statistical machine translation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Oracle decoding as a new way to analyze phrase-based machine translation
Machine Translation
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We present improvements to a greedy decoding algorithm for statistical machine translation that reduce its time complexity from at least cubic (O(n6) when applied naïvely) to practically linear time1 without sacrificing translation quality. We achieve this by integrating hypothesis evaluation into hypothesis creation, tiling improvements over the translation hypothesis at the end of each search iteration, and by imposing restrictions on the amount of word reordering during decoding.