Article published in:
Target
Vol. 22:1 (2010) ► pp. 721
References

References

Allen, Jeff
2003 “Post-editing”. Harold Somers ed. Computers and Translation: A Translator’s Guide. Amsterdam-Philadelphia: John Benjamins. 297–317.  CrossrefGoogle Scholar
Bowker, Lynne, and Melissa Ehgoetz
2007 “Exploring User Acceptance of Machine Translation Output: A Recipient Evaluation”. Dorothy Kenny and Kyongjoo Ryou (eds.) Across Boundaries: International Perspectives on Translation. Newcastle-upon-Tyne: Cambridge Scholars Publishing. 209–224.Google Scholar
Champollion, Yves
2001 “Machine translation and the future of the translation industry”. Translation Journal 5:1.Google Scholar
De Palma, Donald A and Nataly Kelly
2008 “Translation of, for, and by the People”. Common Sense Advisory Report. http://​www​.commonsenseadvisory​.com​/research​/report​_view​.php​? id​=97​&cid​=0#Visited February2010.Google Scholar
Desilets, Alain, Lucas Gonzalez, Sebastien Paquet, Marta Stojanovic
2006 “Translation the Wiki Way.” WikiSym’06, August 21–23, Odense, Denmark. 19–31.Google Scholar
Dillinger, Mike, and Laurie Gerber
2009, January. “Success with Machine Translation. Automating Knowledge-base Translation, Part 1”. Clientside News. 10–11.Google Scholar
Fiederer, Rebecca, and Sharon O’Brien
2009 “Quality and Machine Translation: A realistic objective?” The Journal of Specialised Translation 11. 52–72.Google Scholar
Guerberof, Ana
2009Productivity and quality in the post-editing of outputs from translation memories and machine translation. Localisation Focus 7:1. 11–21.Google Scholar
Lopez, Adam
2008 “Statistical Machine Translation”. AMC Computing Surveys 40:3. 8:1–8:49.Google Scholar
O’Brien, Sharon
2006 “Eye-Tracking and Translation Memory Matches”. Perspectives: Studies in Translatology 14:3. 185–204.Google Scholar
Pym, Anthony
2009 “Using process studies in translator training: self-discovery through lousy experiments”. http://​www​.tinet​.cat​/~apym​/on​-line​/training​/2009​_lousy​_experiments​.pdf Visited February 2010.Google Scholar
SDL Research 2008 “Trends in automated translation in today’s global business”. White Paper. http://​www​.sdl​.com​/en​/globalization​-knowledge​-centre​/whitepapers/. Visited February 2010.Google Scholar
[ p. 21 ]
Zetzsche, Jost
2009July 24. The Tool Kit, 9-7-145. http://​www​.internationalwriters​.com​/toolkit. Visited February2010.Google Scholar
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Flanagan, Marian & Tina Paulsen Christensen
2014. Testing post-editing guidelines: how translation trainees interpret them and how to tailor them for translator training purposes. The Interpreter and Translator Trainer 8:2  pp. 257 ff. Crossref logo
Garcia, Ignacio
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Garcia, Ignacio & María Isabel Pena
2011. Machine translation-assisted language learning: writing for beginners. Computer Assisted Language Learning 24:5  pp. 471 ff. Crossref logo
Groves, Michael & Klaus Mundt
2015. Friend or foe? Google Translate in language for academic purposes. English for Specific Purposes 37  pp. 112 ff. Crossref logo
Guerberof, Ana
2017.  In Translation in Transition [Benjamins Translation Library, 133],  pp. 188 ff. Crossref logo
Huangfu, Wei & Yushan Zhao
2014. A Corpus-based Machine Translation Method of Term Extraction in LSP Texts. Theory and Practice in Language Studies 4:1 Crossref logo
Jiménez-Crespo, Miguel A.
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Killman, Jeffrey
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Koby, Geoffrey S.
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O’Brien, Sharon, Michel Simard & Marie-Josée Goulet
2018.  In Translation Quality Assessment [Machine Translation: Technologies and Applications, 1],  pp. 237 ff. Crossref logo
Pym, Anthony
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Sabbah, Nadia & Reem Alsalem
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Shih, Chung-ling
2016. A New Scenario of Machine Translation: Dynamic Contextual Effects with Diverse Paratextual Application. Theory and Practice in Language Studies 6:6  pp. 1183 ff. Crossref logo
Taylor, Rachel M., Nicola Crichton, Beki Moult & Faith Gibson
2015. A prospective observational study of machine translation software to overcome the challenge of including ethnic diversity in healthcare research. Nursing Open 2:1  pp. 14 ff. Crossref logo
Teixeira, Carlos S. C.
2013.  In Where Humans Meet Machines,  pp. 299 ff. Crossref logo
Temizöz, Ö.
2016. Postediting machine translation output: subject-matter experts versus professional translators. Perspectives 24:4  pp. 646 ff. Crossref logo
Tirkkonen-Condit, Sonja
2011. Translation prototype and how to exploit it in translator education. Across Languages and Cultures 12:2  pp. 157 ff. Crossref logo
Yamada, Masaru
2015. Can college students be post-editors? An investigation into employing language learners in machine translation plus post-editing settings. Machine Translation 29:1  pp. 49 ff. Crossref logo
Yang, Yanxia & Xiangling Wang
2019. Modeling the intention to use machine translation for student translators: An extension of Technology Acceptance Model. Computers & Education 133  pp. 116 ff. Crossref logo
Yang, Yanxia, Xiangling Wang & Qingqing Yuan
2020. Measuring the usability of machine translation in the classroom context. Translation and Interpreting Studies Crossref logo

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