... additional information could be:Simple context information: information ofthe words surrounding the word pair;Syntactic information: part-of-speech in-formation, syntactic constituent, sentencemood;Semantic ... 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 ... Tillmann, S. Vogel, H. Ney, and A. Zubiaga. 1997.A DP-based search using monotone alignments in statistical translation. In Proc. 35th Annual Conf.of the Association for Computational Linguistics,pages...
... new method eliminatingmost of the gap between Kneser-Ney andthose methods.1 Introduction Statistical languagemodels are potentially useful for any language technology task that producesnatural -language ... is a single unknown probability distribution for the amount of quantization error in every N- gram count. If so, the total quantization error for a given context will tend to be proportional to ... 4- gram languagemodels using English data fromthe WMT-06 Europarl corpus (Koehn and Monz,2006). We took 1,003,349 sentences (27,493,499words) for training, and 2000 sentences each for testing...
... Kaufmann, San Fran-cisco, CA.Rion Snow, Brendan O’Connor, Daniel Jurafsky, andAndrew Ng. 2008. Cheap and fast – but is itgood? evaluating non-expert annotations for natu-ral language tasks. In ... 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 a translation of just ... WrenThornton, Jonathan Weese, and Omar Zaidan. 2009.Joshua: An open source toolkit for parsing-based machine translation. In Proceedings of the FourthWorkshop on StatisticalMachine Translation, ...
... 2009.Quadratic-time dependency parsing formachine trans-lation. In Proceedings of the Joint Conference of the47th Annual Meeting of the ACL and the 4th Interna-tional Joint Conference on Natural Language ... speechrecognition, research in statisticalmachine trans-lation has effectively used n- gram word sequence models as language models. Modern phrase-based translation using large scale n- gramlanguagemodels ... Proceedings of the Ninth Ma-chine Translation Summit of the International Associ-ation forMachine Translation. Ciprian Chelba and Frederick Jelinek. 1998. Exploit-ing syntactic structure for language...
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... Chunking. In Proc.CoNLL, pages 63-69.Young-Suk Lee, Bing Zhao and Xiaoqiang Luo. 2010.Constituent reordering and syntax modelsfor English-to-Japanese statisticalmachine translation. In Proc.Coling.Chi-Ho ... canhelp English-Hindi StatisticalMachine Translation. In Proc. IJCNLP.Roy Tromble. 2009. Search and Learning for the Lin-ear Ordering Problem with an Application to Machine Translation. Ph.D. ... Subject-Object-Verb Languages. In Proc. HLT-NAACL, pages 376-384.Richard Zens and Hermann Ney. 2006. Discriminative Reordering ModelsforStatisticalMachine Transla-tion. In Proc. Workshop on Statistical Machine...
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... Association for Computational LinguisticsBilingual Sense Similarity forStatisticalMachineTranslation Boxing Chen, George Foster and Roland Kuhn National Research Council Canada 283 ... string con-sisting of terminal and non-terminal symbols. ~ defines a one-to-one correspondence between non-terminals in α and γ. 1 There has been a lot of work (more details in Section ... performance of Alg2 on Chinese-to-English NIST large data condition and German-to-English WMT task. We can see that IBM model 1 and cosine distance similarity function both obtained significant...
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