... classifi-cation error training forstatisticalmachine translation. In EAMT.C. Wang, M. Collins, and P. Koehn. 2007. Chinese syn-tactic reorderingforstatisticalmachine translation. InEMNLP, pages ... Kucerova. 2005. Clause re-structuring forstatisticalmachine translation. In ACL,pages 531–540.J. Eisner. 2003. Learning non-ismorphic tree mappings for machine translation. In ACL, Sapporo, Japan.Short ... smorgasbordof features forstatisticalmachine translation. In HLT-NAACL 2004: Main Proceedings, pages 161–168.F. J. Och. 2003. Minimum error rate training for statisti-cal machine translation. In...
... 521–528,Sydney, July 2006.c2006 Association for Computational LinguisticsMaximum Entropy Based Phrase Reordering Model forStatisticalMachine Translation Deyi XiongInstitute of Computing ... informa-tion for their movements/reorderings. To test thishypothesis, we calculate the information gain ra-tio (IGR) for boundary words as well as the wholeblocks against the order on the reordering ... sxlin}@ict.ac.cnAbstractWe propose a novel reordering model for phrase -based statisticalmachine transla-tion (SMT) that uses a maximum entropy(MaxEnt) model to predicate reorderingsof neighbor blocks...
... experimental results for a bilingual cor- pus are reported. 1.1 StatisticalMachineTranslation In statisticalmachine translation, the goal of the search strategy can be formulated as follows: ... factor of about 3.5. 963 A DP based Search Algorithm forStatisticalMachineTranslation S. Nieflen, S. Vogel, H. Ney, and C. Tillmann Lehrstuhl fiir Informatik VI RWTH Aachen - University ... problem formachinetranslation systems that use translation models based on hid- den alignments without a monotonicity constraint: (Berger et al., !994) and (Wang and Waibel, 1997). The former...
... Disambiguation Improves StatisticalMachine Translation. In: Proceedings of ACL, Prague. D. Chiang. 2005. A hierarchical phrase -based model for statisticalmachine translation. In: Proceedings ... system, this method is also suitable for syntax- based MT systems and phrase -based MT systems. The only difference is the definition of the context. For a syntax- based system, the context of a rule ... Phrase Selection for SMT. In: Goutte et al (ed.), Learning Machine Translation. MIT Press. K. Gimpel and N. A. Smith. 2008. Rich Source-Side Context forStatisticalMachine Translation. In:...
... source toolkit for parsing -based machine translation. In Proceedings of the FourthWorkshop on StatisticalMachine Translation, pages135–139, Athens, Greece, March. Association for Computational ... Suntec,Singapore, August. Association for ComputationalLinguistics.Gholamreza Haffari, Maxim Roy, and Anoop Sarkar.2009. Active learning forstatistical phrase -based machine translation. In Proceedings ... our “before”system already got the translation correct withoutthe need for the additional phrase translation. Thisis because though the “before” system had neverseen the Urdu expression for...
... segmen-tation formachinetranslation performance. In Pro-ceedings of the Third Workshop on Statistical Ma-chine Translation, pages 224–232, Columbus, Ohio.David Chiang. 2007. Hierarchical phrase -based ... Oflazer. 2006.Initial explorations in English to Turkish statistical machine translation. In Proceedings of the Work-shop on StatisticalMachine Translation, pages 7–14, New York City, New York, ... Creutz, and M. Sade-niemi. 2007. Morphology-aware statistical machine translationbased on morphs induced in an unsuper-vised manner. In MachineTranslation Summit XI,pages 491–498, Copenhagen,...
... Association for Computational Linguistics.Philipp Koehn et al. 2007. Moses: Open source toolkit for statisticalmachine translation. In Proceedings ofthe 45th Annual Meeting of the Association for ... 294–298,Portland, Oregon, June 19-24, 2011.c2011 Association for Computational LinguisticsCorpus Expansion forStatisticalMachineTranslation withSemantic Role Label Substitution RulesQin ... William Dolan. 2004.Monolingual machinetranslationfor paraphrase gen-eration. In Proceedings of EMNLP 2004, pages 142–149, Barcelona, Spain, July. Association for Computa-tional Linguistics.298...
... for Phrase -based StatisticalMachineTranslation Mod-els. In Proc. of the Association forMachine Trans-lation in the Americas (AMTA).P. Koehn. 2004b. Statistical Significance Tests for MachineTranslation ... Spain.Y. Lee. 2004. Morphological Analysis for Statistical Machine Translation. In Proc. of NAACL, Boston,MA.Y. Lee. 2005. IBM StatisticalMachineTranslation for Spoken Languages. In Proc. of International ... 2006.c2006 Association for Computational LinguisticsCombination of Arabic Preprocessing Schemes for StatisticalMachine Translation Fatiha SadatInstitute for Information TechnologyNational...
... mathematics of statisticalmachine translation. Computational Linguistics, 19(2):263–313.Charniak, E., Knight, K., and Yamada, K. (2003). Syntax- based language models forstatisticalmachine translation. ... of features for statisticalmachine translation. In Proceedings of HLT-NAACL 2004.Och, F. J., Tillmann, C., and Ney, H. (1999). Improved align-ment models forstatisticalmachine translation. ... Bleuscore for a baseline system to 26.8% Bleu score for the systemwith reordering, a statistically significant improvement.1 IntroductionRecent research on statisticalmachine translation (SMT)...
... Arabic-English translation task.1 IntroductionIn this paper, we present a block -based model for statis-tical machine translation. A block is a pair of phraseswhich are translations of each other. For ... @us.ibm.comAbstractIn this paper, we present a novel trainingmethod for a localized phrase -based predic-tion model forstatisticalmachine translation (SMT). The model predicts blocks with orien-tation ... pages 557–564,Ann Arbor, June 2005.c2005 Association for Computational LinguisticsA Localized Prediction Model forStatisticalMachine Translation Christoph Tillmann and Tong ZhangIBM T.J....
... entropy approach is outlined inSection 3.2 StatisticalMachine Translation The goal of the translation process in statisti-cal machinetranslation can be formulated as fol-lows: A source language ... andChristoph Tillmann. 1998. A DP -based searchalgorithm forstatisticalmachine translation. InCOLING-ACL ’98: 36th Annual Meeting of the As-sociation for Computational Linguistics and 17thInt. ... problem withinthe statistical framework is to use max-imum entropy methods. In this paper,we present how to use this type of in-formation within a statistical machine translation system....
... 2009.c2009 Association for Computational LinguisticsBilingually Motivated Domain-Adapted Word Segmentation for StatisticalMachine Translation Yanjun Ma Andy WayNational Centre for Language TechnologySchool ... achieves consistently better SMT perfor-mance than character -based segmentation (CS) ondifferent data sizes, which means character -based segmentation is not good enough for this domainwhere the vocabulary ... observe that the ICT and Stanford segmenterconsistently outperform the LDC segmenter. Evenusing 3M sentence pairs for training, the differ-ences between them are still statistically signifi-cant...
... Liu, and Shouxun Lin. 2006. Maxi-mum Entropy based Phrase Reordering Model for Statistical Machine Translation. In Proceedings of the Association for Computational Linguistics, pages 521-528. ... Association for Computational Linguistics, pages 1258–1267,Portland, Oregon, June 19-24, 2011.c2011 Association for Computational Linguistics Hypothesis Mixture Decoding forStatisticalMachineTranslation ... large-scale Chinese-to-English translation tasks. 1 Introduction Besides tremendous efforts on constructing more complicated and accurate models forstatistical machine translation (SMT) (Och and...