Machine translation today

Mikel L. Forcada

Table of contents

Machine translation (MT) is the translation, by means of a computer using suitable software, of a text written in the source language (SL) which produces another text in the target language (TL) which may be called its raw translation. This definition seems to imply that the resulting TL translation may be used as a professional product would, but machine translation and professional translation, even if closely related in purpose, are not interchangeable products (Sager 1994: 261).

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References

Allen, Jeffrey
2003“Post-editing.” In: Somers 2003a. 297–319.  TSB. Crossref logoGoogle Scholar
Arnold, Doug
2003“Why translation is difficult for computers.” In: Somers 2003a. 119–142. Crossref logo  TSBGoogle Scholar
Arnold, Doug J., Balkan, Lorna, Meijer, Siety, Humphreys, R. Lee & Sadler, Louisa
1993Machine translation: an Introductory Guide. London: Blackwells. http://​www​.essex​.ac​.uk​/linguistics​/external​/clmt​/MTbook/ [Accessed 21 July 2010].  TSBGoogle Scholar
Brown, P., Cocke J., Della Pietra S., Della Pietra V., Jelinek F., Mercer R., & Roossin P
1988“A statistical approach to French/English translation.” In Second International Conference on Theoretical and Methodological Issues in Machine Translation of Natural Languages, June 12–14, 1988. Pittsburgh, Pennsylvania: Carnegie Mellon University, Center for Machine Translation. Crossref logoGoogle Scholar
Carl, Michael & Way, Andy
(eds) 2003Recent advances in example-based machine translation. Dordrecht: Kluwer. Crossref logo  TSBGoogle Scholar
Hutchins, John & Somers, Harold
1992An introduction to machine translation. London: Academic Press.Google Scholar
Koehn, Philipp
2009Statistical machine translation. Cambridge: Cambridge University Press. Crossref logo  TSBGoogle Scholar
Lockwood, Rose
2000“Machine translation and controlled authoring at Caterpillar.” In Translating into success: cutting-edge strategies for going multilingual in a global age, R.C. Sprung (ed.), 187–202. Amsterdam & Philadelphia: John Benjamins. Crossref logo  TSBGoogle Scholar
Mitamura, Teruko, Nyberg, Eric H. 3rd, Carbonell, Jaime G
1993“An Efficient Interlingua Translation System for Multi-lingual Document Production.” In Progress in machine translation, Sergei Nirenburg (ed.), 105–117. Amsterdam/ Oxford/ Washington DC: IOS Press; Tokyo: Ohmsha.Google Scholar
Nagao, Makoto
1984“A framework of a mechanical translation between Japanese and English by analogy principle”. In Artificial and human intelligence: edited review papers presented at the international NATO Symposium, October 1981, Lyons, France, Alick Elithorn & Ranan Banerji (eds), 173–180. Amsterdam: North Holland.Google Scholar
Nyberg, Eric, Mitamura, Teruko, Huijsen, Willem-Olaf
2003“Controlled language for authoring and translation.” In: Somers 2003a. 245–282.  TSB. Crossref logoGoogle Scholar
Sager, Juan C
1994Language engineering and translation: consequences of automation. Amsterdam & Philadelphia: John Benjamins. Crossref logo  TSBGoogle Scholar
Schneider, Thomas
1989“The METAL system, status 1989.” In Proceedings of MT Summit II, August 16–18, 1989, Munich, Germany. Frankfurt a.M.: Deutsche Gesellschaft für Dokumentations e.V.; 128–136.Google Scholar
Simard, Michel, Goutte, Cyril, Isabelle, Pierre
2007“Statistical phrase-based post-editing.” In NAACL-HLT-2007 Human Language Technology: the conference of the North American Chapter of the Association for Computational Linguistics, 22–27 April 2007, Rochester, NY. 508–515.. Crossref logoGoogle Scholar
Somers, Harold
(ed.) 2003aComputers and Translation: A translator’s guide. Amsterdam & Philadelphia: John Benjamins. Crossref logo  BoPGoogle Scholar
(ed.) 2003b“An overview of EBMT”, in Carl & Way 2003.. Crossref logoGoogle Scholar