By Robert E. Frederking, Kathryn B. Taylor
The former convention during this sequence (AMTA 2002) took up the subject matter “From examine to genuine Users”, and sought to discover why fresh study on data-driven computer translation didn’t appear to be relocating to undefined. because it became out, the ?rst advertisement items of the data-driven study stream have been simply over the horizon, andintheinterveningtwoyearstheyhavebeguntoappearinthemarketplace. Atthesame time,rule-basedmachinetranslationsystemsareintroducingdata-driventechniquesinto the combination of their items. computing device translation as a software program software has a 50-year background. There are increasingly more interesting deployments of MT, lots of on the way to be exhibited and mentioned on the convention. however the scale of business 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 good fortune for MT. We took person wishes as our subject, and explored how or no matter if industry standards are feeding into study courses. The transition of analysis discoveries to useful use consists of te- nicalquestionsthatarenotassexyasthosethathavedriventheresearchcommunityand examine investment. very important product matters akin to approach customizability, computing source necessities, and value and ?tness for specific projects have to have interaction the creativeenergiesofallpartsofourcommunity,especiallyresearch,aswemovemachine translation from a distinct segment software to a extra pervasive language conversion approach. Thesetopicswereaddressedattheconferencethroughthepaperscontainedinthesep- ceedings, or even extra speci?cally via numerous invited shows and panels.
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Additional info for Machine Translation: From Real Users to Research: 6th Conference of the Association for Machine Translation in the Americas, AMTA 2004, Washington, DC, ...
In Proceedings of HLT 2001, pages 109–116, San Diego, CA, 2001. A Modified Burrows-Wheeler Transform for Highly Scalable Example-Based Translation Ralf D. edu Abstract. The Burrows-Wheeler Transform (BWT) was originally developed for data compression, but can also be applied to indexing text. In this paper, an adaptation of the BWT to word-based indexing of the training corpus for an example-based machine translation (EBMT) system is presented. The adapted BWT embeds the necessary information to retrieve matched training instances without requiring any additional space and can be instantiated in a compressed form which reduces disk space and memory requirements by about 40% while still remaining searchable without decompression.
The remainder of this section presents the linguistic knowledge associated with DUSTer, after which an example of rule application is given. Finally, we describe the combination of DUSTer and GIZA++ in Multi-Align. , classes of verbs including Aspectual, Change of State, Directional, etc. . The parameter classes play an important role in identifying and handling translation divergences. The current classification includes 16 classes of parameters. Because the parameters are based on semantic knowledge, the English values can be projected to their corresponding values in a new language, simply by translating the words into the other language.
21. Kenji Yamada and Kevin Knight. A Syntax-Based Statistical Translation Model. In Proceedings of ACL 2001, Toulouse, France, 2001. 22. David Yarowsky, Grace Ngai, and Richard Wicentowski. Inducing Multilingual Text Analysis Tools via Robust Projection Across Aligned Corpora. In Proceedings of HLT 2001, pages 109–116, San Diego, CA, 2001. A Modified Burrows-Wheeler Transform for Highly Scalable Example-Based Translation Ralf D. edu Abstract. The Burrows-Wheeler Transform (BWT) was originally developed for data compression, but can also be applied to indexing text.