... USAme@hal3.nameAbstractWe present a method to transliterate namesin the framework of end -to- end statistical machine translation. The system is trained to learn when to transliterate. For Arabic to English MT, we developed ... apply it to any base SMT system, and to human translationsas well. Our goal in augment-ing abaseSMT systemis toincreasethis percentage.A secondary goal is to make sure that our overall translation ... name translation quality varies greatlybetween human translators, with error rates ranging from 8.2-15.0% (absolute). To make sure our name transliterator does not de-grade the overall translation...
... POS+clitic factor. We also use a genera-tion model to generate the surface form from thestem and POS+clitic, a translation table from POS to POS+clitics and from the English surface word to the Arabic ... theireffect on translation. We also report on applyingFactored Translation Models (Koehn and Hoang,2007) for English- to- Arabic translation. 2 Previous WorkThe only previous work on English- to- Arabic ... techniques. We also report on the useof Factored Translation Models for English- to- Arabic translation. 1 IntroductionArabic has a complex morphology compared to English. Words are inflected for gender,...
... forGerman -English, Chinese -English, English- Hindiand English- Japanese respectively. Xu et al. (2009)designed a clever precedence reordering rule set for translation fromEnglishto several ... processing 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. ... Reordering for Statistical Ma-chine Translation. In Proc. ACL, pages 720-727.Yang Liu, Qun Liu, and Shouxun Lin. 2006. Tree- to- String Alignment Template for Statistical Machine Translation. ...
... pairs according to the prede-fined topic-specific translation model and thetopic posterior distribution of phrases.Formally, we incorporate monolingual topic in-formation into translation probability ... effectively transferred from one domain to anoth-er, for example, from newswire to weblog.According to adaptation emphases, domain adap-tation in SMT can be classified into translation mod-el ... 2006. Tree- to- String Alignment Template for Statistical Machine Translation. In Proc. of ACL 2006, pages 609-616.Yajuan Lv, Jin Huang and Qun Liu. 2007. Improv-ing StatisticalMachine Translation...
... reordering in Arabic- English statisticalmachine translation. Machine Trans-lation, Published Online.David Chiang. 2005. A hierarchical phrase-based modelfor statisticalmachine translation. In ... have to convert chunk -to- chunk jumps intoword -to- word shortcuts. We propose two ways to do this, given an ordered pair of chunks (cx,cy):mode A×A : create a shortcut from each word ofcx to ... 2011.Fuzzy syntactic reordering for phrase-based statistical machine translation. In Proceedings of the Sixth Work-shop on StatisticalMachine Translation, pages 227–236, Edinburgh, Scotland,...
... april.Nicola Bertoldi and Marcello Federico. 2009. Do-main adaptation for statisticalmachinetranslation withmonolingual resources. In Proceedings of the FourthWorkshop on StatisticalMachine Translation, ... a different approach to select related sen-tences from OUT. They use language model per-plexities from IN to select relavant sentences from OUT. These sentences are used to enrich the INtraining ... Alfons Juan. 2007. Domain adap-tation in statisticalmachinetranslation with mixturemodelling. In Proceedings of the Second Workshopon StatisticalMachine Translation, StatMT ’07, pages177–180,...
... train a Chinese -to -English SMT system, we need to perform both Chinese -to -English and English- to- Chinese word alignment. We only evaluate the English- to- Chinese word alignment here. GIZA++ with ... corpus to train the Chinese -to- English SMT systems. Moses (Koehn et al., 2007) is used as the baseline phrase-based SMT system. We use SRI language modeling toolkit (Stolcke, 2002) to train ... model in addition to the word translation model and position distribution model. And these three models are similar, ex-cept for the word distortion models. One -to- one and many -to- one alignments...
... large data Chinese -to- English NIST task and German -to -English WMT task. 6 We have also conducted additional experiments by remov-ing the stop words from the context vectors; however, we ... and target sides of a translation rule to improve statisticalmachinetranslation perfor-mance. This work attempts to measure directly the sense similarity for units from different languag-es ... as feature functions in the translation model. 5.1 Data We evaluated with different language pairs: Chi-nese -to -English, and German -to -English. For Chinese -to -English tasks, we carried out...
... 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, ... unlabeled pool from which to gather annotations. We applied theHNG method from Section 4 to determine what to post on MTurk for workers to translate.2We gath-ered 20,580 n-gram translations ... Discussion5.1 General SetupWe set out to see whether we could use the HNGmethod to achieve translation quality improve-ments by gathering additional translations to add to the training data of the entire...
... Kemal Oflazer. 2006.Initial explorations in EnglishtoTurkish statistical machine translation. In Proceedings of the Work-shop on StatisticalMachine Translation, pages 7–14, New York City, New ... from morphologically-rich Turkishto English does not exhibit the expected im-provement in translation BLEU scores andconfirms the robustness of phrase-basedSMT totranslation unit combinatorics.A ... Mor-phological Pre-Processing for TurkishtoEnglish Statistical Machine Translation. In Proc. of the In-ternational Workshop on Spoken Language Transla-tion, pages 129–135, Tokyo, Japan.M.R. Brent....
... on Chinese- English machinetranslation tasks show an av-erage improvement of 0.45 BLEU and 1.22TER points across 5 different NIST test sets.1 Introduction Statistical machinetranslation ... Chinese -English machine translation tasks and the performance iscomparable to system trained with larger manuallycollected parallel corpus. While our experimentswere performed on Chinese -English, ... Association for Computational Linguistics.Philipp Koehn et al. 2007. Moses: Open source toolkitfor statisticalmachine translation. In Proceedings ofthe 45th Annual Meeting of the Association for Com-putational...