Machine Translation and the World Wide Web

Part of the Text, Speech and Language Technology book series (TLTB, volume 36)


World Wide Machine Trans Target Language Source Text Language Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Anderson, D.D. (1995) Machine translation as a tool in second language learning. CALICO Journal 13(1):68–97.Google Scholar
  2. Anon. (2003) More machine translation: Fun with computer generated translation! Biomedical Translations, News, October 2003. Scholar
  3. Anon. (2005) Gotcha!: Translation software. Software that translates text from one language to another may be a big help—or hindrance—to businesses and relief agencies alike. Baseline, May 2, 2005.,1397,1791588,00.asp.Google Scholar
  4. Baayen, R.H. (2001) Word Frequency Distributions. Dordrecht: Kluwer Academic Publishers.Google Scholar
  5. Babych, B. and A. Hartley (2004) Selecting translation strategies in MT using automatic named entity recognition. In 9th EAMT Workshop “Broadening Horizons of Machine Translation and its Applications”, Valletta, Malta, 18–25.Google Scholar
  6. Bernth, A. (1999a) EasyEnglish: A confidence index for MT. In Proceedings of the 8th International Conference on Theoretical and Methodological Issues in Machine Translation, TMI ’99, Chester, England, 120–127.Google Scholar
  7. Bernth, A. (1999b) Controlling input and output of MT for greater user acceptance. In Translating and the Computer 21, London, [pages not numbered].Google Scholar
  8. Bernth, A. and C. Gdaniec (2002) MTranslatability. Machine Translation 16, 175–218.CrossRefGoogle Scholar
  9. Bernth, A. and M. McCord (2000) The effect of source analysis on translation confidence. In J.S. White (ed.), Envisioning Machine Translation in the Information Future: 4th Conference of the Association for Machine Translation in the Americas, AMTA 2000, Cuernavaca, Mexico,…, Berlin: Springer, 89–99.Google Scholar
  10. Brin, S., J. Davis and H. Garcia-Molina (1995) Copy detection mechanisms for digital documents. In Proceedings of the 1995 ACM SIGMOD International Conference on Management of Data, San Jose, California, 398–409.CrossRefGoogle Scholar
  11. Clough, P. (2003) Old and new challenges in automatic plagiarism detection. JISC National Plagiarism Advisory Service, Newcastle-upon-Tyne, Available online at Scholar
  12. Clough, P., R. Gaizauskas, S.L. Piao and Y. Wilks (2002) METER: MEasuring TExt Reuse. In ACL-02: 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, PA, 152–159.Google Scholar
  13. Doddington, G. (2002) Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. In HLT 2002 Human Language Technology Conference, San Diego, CA.Google Scholar
  14. Farwell, D. and Y. Wilks (1991) ULTRA: A multilingual machine translator. In Machine Translation Summit III Proceedings, Washington, DC, 19–24.Google Scholar
  15. Flanagan, M. (1996) Two years online: experiences, challenges and trends. In Expanding MT Horizons: Proceedings of the Second Conference of the Association for Machine Translation in the Americas, Montreal, Canada, 192–197.Google Scholar
  16. Gaspari, F. (2004a) Integrating on-line MT services into monolingual web-sites for dissemination purposes: An evaluation perspective. In 9th EAMT Workshop “Broadening horizons of machine translation and its applications”, Valletta, Malta, 62–72.Google Scholar
  17. Gaspari, F. (2004b) ‘On-line MT services and real users’ needs: An empirical usability evaluation’ in R.E. Federking and K.B. Taylor (eds.) Machine Translation from real users to research. LNAI 3265 Berlin, Springer, 74–85.Google Scholar
  18. Gdaniec, C. (1994) The Logos translatability index. In Proceedings of the First Conference of the Association for Machine Translation in the Americas, Columbia, Maryland, 97–105.Google Scholar
  19. Heintze, N. (1996) Scalable document fingerprinting. In Proceedings of the Second USENIX Workshop on Electronic Commerce, Oakland, California.Google Scholar
  20. Helmreich, S., L. Guthrie and Y. Wilks (1993) The use of machine readable dictionaries in the Pangloss project. In Building Lexicons for Machine Translation: Papers from the AAAI Spring Symposium, Stanford University, CA, 63–68.Google Scholar
  21. Krug, S. (2000) Don’t Make Me Think: A Common Sense Approach to Web Usability. Indianapolis, IN: New Riders.Google Scholar
  22. Langlais, P., S. Gandrabur, T. Leplus and G. Lapalme (2005) The long-term forecast for weather bulletin translation. Machine Translation 19:83–112.CrossRefGoogle Scholar
  23. Levenshtein, V.I. (1965) {\vchar{04C}}{\vchar{065}}{\vchar{076}}{\vchar{065}}{\vchar{06E}}{\vvg\char"057}{\vchar{074}}{\vchar{065}}{\vchar{01A}}{\vchar{06E}}, B.{\vchar{049}}. {\vchar{044}}{\vchar{076}}{\vchar{06F}}{\vchar{069}}{\vchar{071}}{\vchar{06E}}{\vchar{079}}{\vchar{065}} {\vchar{06B}}{\vchar{06F}}{\vchar{064}}{\vchar{079}} {\vchar{073}} {\vchar{069}}{\vchar{073}}{\vchar{070}}{\vchar{072}}{\vchar{061}}{\vchar{076}}{\vchar{06C}}{\vchar{065}}{\vchar{06E}}{\vchar{069}}{\vchar{065}}{\vchar{06D}} {\vchar{076}}{\vchar{079}}{\vchar{070}}{\vchar{061}}{\vchar{064}}{\vchar{065}}{\vchar{06E}}{\vchar{069}}{\vchar{01A}}, {\vchar{076}}{\vchar{073}}{\vchar{074}}{\vchar{061}}{\vchar{076}}{\vchar{06F}}{\vchar{06B}} {\vchar{069}} {\vchar{07A}}{\vchar{061}}{\vchar{06D}}{\vchar{065}}{\vvg\char"057}{\vchar{065}}{\vchar{06E}}{\vchar{069}}{\vchar{001A}} {\vchar{073}}{\vchar{069}}{\vchar{06D}}{\vchar{076}}{\vchar{06F}}{\vchar{06C}}{\vchar{06F}}{\vchar{076}}. {\vichar{044}}{\vichar{06F}}{\vichar{06B}}{\vvgfont\char"04C}{\vichar{061}}{\vichar{064}}{\vichar{079}} {\vichar{041}}{\vichar{06B}}{\vichar{061}}{\vichar{064}}{\vichar{065}}{\vichar{06D}}{\vichar{069}}{\vichar{01A}} {\vichar{04E}}{\vichar{061}}{\vichar{075}}{\vichar{06B}} %{\spchar{045}}{\spchar{063}}{\spchar{06F}}{\spchar{069}}{\spchar{078}}{\spchar{06E}}{\spchar{07C}}{e} {{\UPkappa}}{\spchar{06F}}{\spchar{065}}{\spchar{07D}}{\fontsize{6}{8}\selectfont{I}} %{\spchar{072}} {\spchar{069}}{\spchar{072}}{\spchar{070}}{\spchar{071}}{\spchar{061}}{\spchar{063}}{\spchar{06C}}{\spchar{066}}{\spchar{06E}}{\spchar{069}}{\spchar{066}}{\spchar{06D}} %{\spchar{063}}{\spchar{07D}}{\fontsize{6}{8}\selectfont{I}}{\spchar{070}}{\spchar{061}}{\spchar{065}}{\spchar{066}}{\spchar{06E}}{\spchar{069}}{\spchar{06A}}, %{\spchar{063}}{\spchar{072}}{\spchar{073}}{\spchar{061}}{\spchar{063}}{\spchar{06F}}{\UPkappa} %{\spchar{069}} %{\spchar{068}}{\spchar{061}}{\spchar{06D}}{\spchar{066}}{\spchar{07A}}{e}{\spchar{06E}}{\spchar{069}}{\spchar{06A}} %{\spchar{072}}{\spchar{069}}{\spchar{06D}}{\spchar{063}}{\spchar{06F}}{\spchar{06C}}{\spchar{06F}}{\spchar{063}}. %{\spichar{045}}{\spchar{06F}}{κ}alebox{.7[.7]{{\spismchar{04C}}}}a∂{\spichar{07C}} %A{κ}ae{\spichar{06D}}u{\spichar{06A}} Hay{κ CCCP 163(4):845–848. Appeared as: Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady 10 (1966):707–710.Google Scholar
  24. Lyon, C., J. Malcolm and B. Dickerson (2001) Detecting short passages of similar text in large document collections. In 2001 Conference on Empirical Methods in Natural Language Processing (EMNLP 2001), Pittsburgh, PA, 118–125.Google Scholar
  25. Macklovitch, E. (2001) Recent trends in translation technology. In Proceedings of the 2nd International Conference, The Translation Industry Today: Multilingual Documentation, Technology, Market, Bologna, Italy, 23–47.Google Scholar
  26. McCarthy, B. (2004) Does online machine translation spell the end of take-home translation assignments? CALL-EJ Online 6. 1. Available at english/callejonline/9-1/mccarthy.html.Google Scholar
  27. Miyazawa, S., aS. Yokoyama, M. Matsudaira, A. Kumano, S. Kodama, H. Kashioka, Y. Shirokizawa and Y. Nakajima (1999) Study on evaluation of WWW MT systems. In Proceedings of MT Summit VII “MT in the Great Translation Era”, Singapore, 290–298.Google Scholar
  28. Nielsen, J. (2000) Designing Web Usability: The Practice of Simplicity. Indianapolis, IN: New Riders.Google Scholar
  29. Niño, A. (2004) Recycling MT: A course on foreign language writing via MT post-editing. In 7th Annual CLUK Research Colloquium, Birmingham. [pages not numbered]Google Scholar
  30. Nunberg, G. (2005) Letting the Net speak for itself: Fears of an ‘anglo-saxon’ takeover of the online world are unfounded. San Jose Mercury News, April 17, 2005, available at∼nunberg/weblg.html.Google Scholar
  31. O’Brien, S. (2005) Methodologies for measuring the correlations between post-editing effort and machine translatability. Machine Translation 19:37–58.CrossRefGoogle Scholar
  32. O’Connell, T.A. (2001) Preparing your web site for machine translation: How to avoid losing (or gaining) something in the translation. IBM website, developerworks/web/library/us-mt/.Google Scholar
  33. Papineni, K., S. Roukos, T. Ward and W. Zhu (2002) BLEU: A method for automatic evaluation of machine translation. In ACL-02: 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, PA, 311–318.Google Scholar
  34. Richmond, I.M. (1994) Doing it backwards: Using translation software to teach target-language grammaticality. Computer Assisted Language Learning 7:65–78.Google Scholar
  35. Shivakumar, N. and H. Garcia-Molina (1996) Building a scalable and accurate copy detection mechanism. In DL’96: First ACM Conference on Digital Libraries, Bethesda, MD.Google Scholar
  36. Somers, H. (2001) Three perspectives on MT in the classroom. In MT Summit VIII Workshop on Teaching Machine Translation, Santiago de Compostela, 25–29.Google Scholar
  37. Somers, H. (2005) Round-trip translation: What is it good for? In Australasian Language Technology Workshop 2005, Sydney, Australia, 127–133.Google Scholar
  38. Somers, H., F. Gaspari and A. Niño (2006) Detecting inappropriate use of free online machine translation by language students – A special case of plagiarism detection. In 11th Annual Conference of the European Association for Machine Translation – Proceedings, Oslo, 41–48.Google Scholar
  39. Turian, J.P., L. Shen and I.D. Melamed (2003) Evaluation of machine translation and its evaluation. In MT Summit IX: Proceedings of the Ninth Machine Translation Summit, New Orleans, LA, 23–28.Google Scholar
  40. Underwood, N. and B. Jongejan. (2001) Translatability checker: A tool to help decide whether to use MT. In Proceedings of MT Summit VIII: Machine Translation in the Information Age, Santiago de Compostela, Spain, 363–368.Google Scholar
  41. Wilks, Y. (1973a) An artificial intelligence approach to machine translation. In R.C. Schank and K.M. Colby (eds.), Computer Models of Thought and Language, San Francisco: Freeman, 114–151.Google Scholar
  42. Wilks, Y. (1973b) The Stanford machine translation project. In R. Rustin (ed.), Natural Language Processing, New York: Algorithmics Press, 243–290; repr. in S. Nirenburg, H. Somers and Y. Wilks (eds.) (2003) Readings in Machine Translation, Cambridge. MA: MIT Press, 371–390.Google Scholar
  43. Wilks, Y. (1975a) An intelligent analyzer and understander of English. Communications of the ACM 18:264–274.CrossRefGoogle Scholar
  44. Wilks, Y. (1975b) Preference semantics. In E. Keenan (ed.), Formal Semantics of Natural Language, Cambridge: Cambridge University Press, 329–348.Google Scholar
  45. Wilks, Y. (1978) Comparative translation quality analysis (Final report F-33657-77-C-0695), Latsec Inc., La Jolla, CA.Google Scholar
  46. Wilks, Y. (1990a) Form and content in semantics. Synthese 82:329–351.CrossRefGoogle Scholar
  47. Wilks, Y. (1990b) Themes in the work of Margaret Masterman. In P. Mayorcas (ed.), Translating and the Computer 10: The Translation Environment 10 years on, London: Aslib, 148–160.Google Scholar
  48. Wilks, Y. (1992a) SYSTRAN: It obviously works, but how much can it be improved? In J. Newton (ed.), Computers and Translation: A Practical Appraisal, London: Routledge, 166–188.Google Scholar
  49. Wilks, Y. (1992b) Pangloss: A knowledge-based machine assisted translation research project – Site 2, In Speech and Natural Language: Proceedings of a Workshop, Harriman, New York, 280.Google Scholar
  50. Wilks, Y. (1992c) Stone soup and the French room: The empiricist-rationalist debate about machine translation. Talk given at TMI 92, Montreal. First published (1993) as Memorandum in Computer and Cognitive Science MCCS-93-255, Computing Research Laboratory, New Mexico State University, Las Cruces, NM; repr. (1994) In A. Zampolli, N. Calzolari and M. Palmer (eds.), Current Issues in Computational Linguistics: In Honor of Don Walker, Pisa/Dordrecht: Giardini/Kluwer, 585–595.Google Scholar
  51. Wilks, Y. (1994) Developments in machine translation in the US. Aslib Proceedings 46:111–116.CrossRefGoogle Scholar
  52. Wilks, Y. (2000) Margaret Masterman. In W. J. Hutchins (ed.), Early Years in Machine Translation: Memoirs and Biographies of Pioneers, Amsterdam: John Benjamins, 279–297.Google Scholar
  53. Woolls, D. and M. Coulthard (1998) Tools for the trade. Forensic Linguistics 5:33–57.CrossRefGoogle Scholar
  54. Yang, J. and Lange, E.D. (1998) Systran on AltaVista: A user study on real-time machine translation on the Internet. In D. Farwell, L. Gerber and E. Hovy (eds.), Machine Translation and the Information Soup: Third Conference of the Association for Machine Translation in the Americas, AMTA’98, Langhorne, PA, Berlin: Springer, 275–285.Google Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  1. 1.School of Informatics, University of ManchesterManchesterUK

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