Machine Translation: From Real Users to Research: 6th by Jeffrey Allen (auth.), Robert E. Frederking, Kathryn B.

Machine Translation: From Real Users to Research: 6th by Jeffrey Allen (auth.), Robert E. Frederking, Kathryn B.

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

The earlier convention during this sequence (AMTA 2002) took up the topic “From study to actual Users”, and sought to discover why contemporary examine on data-driven laptop translation didn’t appear to be relocating to undefined. because it became out, the ?rst advertisement items of the data-driven study circulation have been simply over the horizon, andintheinterveningtwoyearstheyhavebeguntoappearinthemarketplace. Atthesame time,rule-basedmachinetranslationsystemsareintroducingdata-driventechniquesinto the combination of their items. computing device translation as a software program program has a 50-year historical past. There are progressively more fascinating deployments of MT, lots of in an effort 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 your next step within the route to advertisement luck for MT. We took consumer wishes as our subject, and explored how or no matter if marketplace necessities are feeding into study courses. The transition of analysis discoveries to functional use consists of te- nicalquestionsthatarenotassexyasthosethathavedriventheresearchcommunityand learn investment. very important product concerns comparable to procedure customizability, computing source requisites, 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 a number of 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, USA, September 28 - October 2, 2004. Proceedings

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An Unsupervised Method for Word Sense Tagging Using Parallel Corpora. In Proceedings of ACL 2002, Philadelphia, PA, 2002. 5. Bonnie J. Dorr, Lisa Pearl, Rebecca Hwa, and Nizar Habash. DUSTer: A Method for Unraveling Cross-Language Divergences for Statistical Word–Level Alignment. In Proceedings of AMTA 2002, Tiburon, CA, 2002. 6. Jason Eisner. Learning Non-isomorphic Tree Mappings for Machine Translation. In Proceedings of ACL 2003, Supporo, Japan, July 2003. 7. Joshua Goodman. Parsing Algorithm and Metrics.

Table 1 clearly shows the O(N) performance of the old index and the much better scaling of the new BWT-based index for the Hindi and Arabic test sets. The times listed are the amount of time required to locate all matching in the input sentences, without retrieving any of the matches from the corpus. The French test set also illustrates that the nature of the text influences the lookup time, since the French training text is much closer to the test sentences than is the case for the other languages, and as a result there are many more matches – and, in particular, long matches – against the corpus.

Ker and Jason S. Chang. A Class-based Approach to Word Alignment. Computational Linguistics, 23(2):313–343, 1997. 12. Philip Koehn, Franz Josef Och, and Daniel Marcu. Statistical Phrase-Based Translation. In Proceedings of NAACL/HLT 2003, Edmonton, Canada, 2003. 13. Beth Levin. English Verb Classes and Alternations: A Preliminary Investigation. University of Chicago Press, Chicago, IL, 1993. 14. Mitchell Marcus, Beatrice Santorini, and Mary Ann Marcinkiewicz. Building a Large Annotated Corpus of English: the Penn Treebank.

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