LEADER 07332nam 22007935 450 001 9910144347403321 005 20200630010556.0 010 $a3-540-30194-1 024 7 $a10.1007/b100780 035 $a(CKB)1000000000212572 035 $a(DE-He213)978-3-540-30194-3 035 $a(SSID)ssj0000195110 035 $a(PQKBManifestationID)11166645 035 $a(PQKBTitleCode)TC0000195110 035 $a(PQKBWorkID)10242431 035 $a(PQKB)11063431 035 $a(MiAaPQ)EBC3087442 035 $a(PPN)155185624 035 $a(EXLCZ)991000000000212572 100 $a20121227d2004 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Translation: From Real Users to Research $e6th Conference of the Association for Machine Translation in the Americas, AMTA 2004, Washington, DC, USA, September 28-October 2, 2004, Proceedings /$fedited by Robert E. Frederking, Kathryn B. Taylor 205 $a1st ed. 2004. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2004. 215 $a1 online resource (VIII, 284 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v3265 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-23300-8 320 $aIncludes bibliographical references and index. 327 $aCase Study: Implementing MT for the Translation of Pre-sales Marketing and Post-sales Software Deployment Documentation at Mycom International -- A Speech-to-Speech Translation System for Catalan, Spanish, and English -- Multi-align: Combining Linguistic and Statistical Techniques to Improve Alignments for Adaptable MT -- A Modified Burrows-Wheeler Transform for Highly Scalable Example-Based Translation -- Designing a Controlled Language for the Machine Translation of Medical Protocols: The Case of English to Chinese -- Normalizing German and English Inflectional Morphology to Improve Statistical Word Alignment -- System Description: A Highly Interactive Speech-to-Speech Translation System -- A Fluency Error Categorization Scheme to Guide Automated Machine Translation Evaluation -- Online MT Services and Real Users? Needs: An Empirical Usability Evaluation -- Counting, Measuring, Ordering: Translation Problems and Solutions -- Feedback from the Field: The Challenge of Users in Motion -- The Georgetown-IBM Experiment Demonstrated in January 1954 -- Pharaoh: A Beam Search Decoder for Phrase-Based Statistical Machine Translation Models -- The PARS Family of Machine Translation Systems for Dutch System Description/Demonstration -- Rapid MT Experience in an LCTL (Pashto) -- The Significance of Recall in Automatic Metrics for MT Evaluation -- Alignment of Bilingual Named Entities in Parallel Corpora Using Statistical Model -- Weather Report Translation Using a Translation Memory -- Keyword Translation from English to Chinese for Multilingual QA -- Extraction of Name and Transliteration in Monolingual and Parallel Corpora -- Error Analysis of Two Types of Grammar for the Purpose of Automatic Rule Refinement -- The Contribution of End-Users to the TransType2 Project -- An Experiment on Japanese-Uighur Machine Translation and Its Evaluation -- A Structurally Diverse Minimal Corpus for Eliciting Structural Mappings Between Languages -- Investigation of Intelligibility Judgments -- Interlingual Annotation for MT Development -- Machine Translation of Online Product Support Articles Using a Data-Driven MT System -- Maintenance Issues for Machine Translation Systems -- Improving Domain-Specific Word Alignment with a General Bilingual Corpus -- A Super-Function Based Japanese-Chinese Machine Translation System for Business Users. 330 $aThe previous conference in this series (AMTA 2002) took up the theme ?From Research to Real Users?, and sought to explore why recent research on data-driven machine translation didn?t seem to be moving to the marketplace. As it turned out, the ?rst commercial products of the data-driven research movement were just over the horizon, andintheinterveningtwoyearstheyhavebeguntoappearinthemarketplace. Atthesame time,rule-basedmachinetranslationsystemsareintroducingdata-driventechniquesinto the mix in their products. Machine translation as a software application has a 50-year history. There are an increasing number of exciting deployments of MT, many of which will be exhibited and discussed at the conference. But the scale of commercial use has never approached the estimates of the latent demand. In light of this, we reversed the question from AMTA 2002, to look at the next step in the path to commercial success for MT. We took user needs as our theme, and explored how or whether market requirements are feeding into research programs. The transition of research discoveries to practical use involves te- nicalquestionsthatarenotassexyasthosethathavedriventheresearchcommunityand research funding. Important product issues such as system customizability, computing resource requirements, and usability and ?tness for particular tasks need to engage the creativeenergiesofallpartsofourcommunity,especiallyresearch,aswemovemachine translation from a niche application to a more pervasive language conversion process. Thesetopicswereaddressedattheconferencethroughthepaperscontainedinthesep- ceedings, and even more speci?cally through several invited presentations and panels. 410 0$aLecture Notes in Artificial Intelligence ;$v3265 606 $aTranslation and interpretation 606 $aArtificial intelligence 606 $aMathematical logic 606 $aNatural language processing (Computer science) 606 $aTranslation$3https://scigraph.springernature.com/ontologies/product-market-codes/N47000 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 610 1 $aMachine translation 610 1 $aReal users 610 1 $aAMTA 610 2 $aAmericas 615 0$aTranslation and interpretation. 615 0$aArtificial intelligence. 615 0$aMathematical logic. 615 0$aNatural language processing (Computer science). 615 14$aTranslation. 615 24$aArtificial Intelligence. 615 24$aMathematical Logic and Formal Languages. 615 24$aNatural Language Processing (NLP). 615 24$aNatural Language Processing (NLP). 676 $a418/.02/0285 702 $aFrederking$b Robert E$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTaylor$b Kathryn B$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 02$aAssociation for Machine Translation in the Americas. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910144347403321 996 $aMachine Translation: From Real Users to Research$92281403 997 $aUNINA