... Disambiguation Improves StatisticalMachine Translation. In: Proceedings of ACL, Prague. D. Chiang. 2005. A hierarchical phrase-based model for statisticalmachine translation. In: Proceedings ... 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: ... Association for Computational Linguistics, pages 834–843,Uppsala, Sweden, 11-16 July 2010.c2010 Association for Computational LinguisticsBilingual Sense Similarity forStatisticalMachine Translation...
... source toolkit for parsing-based machine translation. In Proceedings of the FourthWorkshop on StatisticalMachine Translation, pages135–139, Athens, Greece, March. Association for Computational ... 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 ... HNG, for short.HNG solicits translations only for trigger n-gramsand not for entire sentences. We provide senten-tial context, highlight the trigger n-gram that wewant translated, and ask for...
... 2008. Optimizing Chinese word segmen-tation formachinetranslation performance. In Pro-ceedings of the Third Workshop on Statistical Ma-chine Translation, pages 224–232, Columbus, Ohio.David ... 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, ... 31–36,Uppsala, Sweden, 13 July 2010.c2010 Association for Computational LinguisticsUnsupervised Search for The Optimal Segmentation for Statistical Machine Translation Cos¸kun Mermer1,3and Ahmet Afs¸ın...
... 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 ... Association for Computational Linguistics:shortpapers, pages 294–298,Portland, Oregon, June 19-24, 2011.c2011 Association for Computational LinguisticsCorpus Expansion forStatisticalMachineTranslation ... 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...
... 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. ... mathematics of statisticalmachine translation. Computational Linguistics, 19(2):263–313.Charniak, E., Knight, K., and Yamada, K. (2003). Syntax-basedlanguage models forstatisticalmachine translation. ... statisticalmachine translation. In Proceed-ings of EMNLP 2002.Melamed, I. D. (2004). Statisticalmachinetranslation by pars-ing. In Proceedings of ACL 2004.Niessen, S. and Ney, H. (2004). Statistical...
... 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 ... the lexicon models used in statistical machinetranslation systemsdo not include any kind of linguisticor contextual information, which oftenleads to problems in performing a cor-rect word ... 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 statisticalmachine translation system....
... 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: ... 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 of Technology ... easy-to-use measure of the translation performance, the Levenshtein distance between the produced translations and the sample translations was calculated. The translation results are summarized...
... 2009.c2009 Association for Computational LinguisticsBilingually Motivated Domain-Adapted Word Segmentation for StatisticalMachine Translation Yanjun Ma Andy WayNational Centre for Language TechnologySchool ... 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 ... LDC seg-menter2and Stanford segmenter version 2006-05-113. Both ICTCLAS and Stanford segmentersutilise machine learning techniques, with HiddenMarkov Models for ICT (Zhang et al., 2003)...
... for Statistical Machine Translation. In Proceedings of the Association for Computational Linguistics, pages 521-528. Yang Ye, Ming Zhou, and Chin-Yew Lin. 2007. Sen-tence Level MachineTranslation ... 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...
... classifi-cation error training forstatisticalmachine translation. In EAMT.C. Wang, M. Collins, and P. Koehn. 2007. Chinese syn-tactic reordering forstatisticalmachine translation. InEMNLP, pages ... 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 ... 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...
... during translation. This indicatesthat boundary words of blocks may keep informa-tion for their movements/reorderings. To test thishypothesis, we calculate the information gain ra-tio (IGR) for ... 521–528,Sydney, July 2006.c2006 Association for Computational LinguisticsMaximum Entropy Based Phrase ReorderingModel forStatisticalMachine Translation Deyi XiongInstitute of Computing ... k-best list is very important for the minimum error rate training (Och, 2003a)which is used for tuning the weights λ for ourmodel. We use a very lazy algorithm for the k-bestlist generation,...