By Jeffrey Allen (auth.), Robert E. Frederking, Kathryn B. Taylor (eds.)

The prior convention during this sequence (AMTA 2002) took up the subject “From learn to genuine Users”, and sought to discover why contemporary learn on data-driven laptop translation didn’t appear to be relocating to undefined. because it grew to become out, the ?rst advertisement items of the data-driven examine flow have been simply over the horizon, andintheinterveningtwoyearstheyhavebeguntoappearinthemarketplace. Atthesame time,rule-basedmachinetranslationsystemsareintroducingdata-driventechniquesinto the combo of their items. laptop translation as a software program program has a 50-year historical past. There are increasingly more intriguing deployments of MT, lots of in an effort to be exhibited and mentioned on the convention. however the scale of industrial use hasn't ever approached the estimates of the latent call for. In mild of this, we reversed the query from AMTA 2002, to examine the next move within the route to advertisement luck for MT. We took person wishes as our topic, and explored how or even if marketplace specifications are feeding into examine courses. The transition of analysis discoveries to sensible use contains te- nicalquestionsthatarenotassexyasthosethathavedriventheresearchcommunityand learn investment. vital product matters akin to procedure customizability, computing source specifications, and usefulness and ?tness for specific initiatives have to have interaction the creativeenergiesofallpartsofourcommunity,especiallyresearch,aswemovemachine translation from a distinct segment software to a extra pervasive language conversion technique. Thesetopicswereaddressedattheconferencethroughthepaperscontainedinthesep- ceedings, or even extra speci?cally via a number of invited shows and panels.

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Extra info for Machine Translation: From Real Users to Research: 6th Conference of the Association for Machine Translation in the Americas, AMTA 2004, Washington, DC, USA, September 28 - October 2, 2004. Proceedings

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Each entry of say is given a probability of showing the probability that the corresponding words and are aligned together. We also assume that each word alignment system is associated with a confidence value for every pair of aligned words. ), and may be the link class. The contribution of the aligner to a specific entry of the final word alignment matrix is Thus, For a given confidence threshold and are aligned together if The model includes the parameters, and to decide whether two words are aligned to each other or not in this framework.

Firstly, as is known, natural language often permits an enormous amount of expression variation and allows sentences that are structurally complicated. This property of natural language often makes things much more complex, especially when one language is translated into another one either by human translators or by machine. In addition different writers tend to use specialized vocabulary (jargons), special styles and grammatical structures according to their language level or the given geographical environments while writing the documents [10].

In Proceedings of ACL 1996, Santa Cruz, CA, 1996. 8. Nizar Habash. Generation Heavy Hybrid Machine Translation. In Proceedings of INLG 2002, New York, NY, 2002. 9. Nizar Habash and Bonnie J. Dorr. A Categorial Variation Database for English. In Proceedings of NAACL/HLT 2003, pages 96–102, Edmonton, Canada, 2003. 10. Rebecca Hwa, Philip Resnik, Amy Weinberg, and Okan Kolak. Evaluating Translational Correspondence Using Annotation Projection. In Proceedings of ACL 2002, pages 392–399, Philadelphia, PA, 2002.

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