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3 - Translation and Technology

from Part I - The Nature of Translation

Published online by Cambridge University Press:  10 March 2022

By
Akiko Sakamoto
Edited by
Kirsten Malmkjær
Kirsten Malmkjær
Affiliation:
University of Leicester
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Summary

Chapter 3 describes major advances in translation technologies and explains how these have influenced our understanding of translation, particularly the concept of translation quality and the translation production process. Sakamoto argues that these changes have created a rift between translation studies theories and a new notion of translation circulating in the industry. The chapter identifies new trends in translation studies research which seek to develop new knowledge to address this rift.

Keywords

Translation qualitytranslation production processrift between theories and industry
Type
Chapter
Information
The Cambridge Handbook of Translation , pp. 55 - 74
Publisher: Cambridge University Press
Print publication year: 2022

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References

Austermühl, F. (2014). Electronic Tools for Translators. Abingdon: Routledge. Available at http://capitadiscovery.co.uk/port/items/1133149.Google Scholar
Baker, M. (2018/1992). In Other Words: A Coursebook on Translation, 3rd ed. London: Routledge. Available at http://capitadiscovery.co.uk/port/items/1276427.Google Scholar
Bawden, R., Sennrich, R., Birch, A., and Haddow, B. (2018). Evaluating discourse phenomena in neural machine translation. In Proceedings of NAACL-HLT 2018 (pp. 1304–13). Available at http://arxiv.org/abs/1711.00513.Google Scholar
Bourdieu, P. (1979). La distinction. Critique sociale du jugement. Paris: Minuit.Google Scholar
Bourdieu, P. (1984). Distinction: A Social Critique of the Judgement of Taste. London: Routledge and Kegan Paul.Google Scholar
Bowker, L. (2002). Translation-memory systems. In Bowker, L., ed. Computer-Aided Translation Technology: A Practical Introduction. Ottawa: University of Ottawa Press, pp. 93–128.Google Scholar
Bowker, L. (2005). Productivity vs. quality? A pilot study on the impact of translation memory systems. Localization Focus, 4(1), 13–20. Available at www.localisation.ie/sites/default/files/publications/Vol4_1Bowker.pdf.Google Scholar
Bowker, L. (2006). Translation memory and ‘text’. In Bowker, L., ed., Lexicography, Terminology, and Translation: Text-Based Studies in Honour of Ingrid Meyer. Ottawa: University of Ottawa Press, pp. 175–87.CrossRefGoogle Scholar
Bowker, L. (2019). Fit-for-purpose translation. In O’Hagan, M., ed., The Routledge Handbook of Translation and Technology London: Taylor and Francis, pp. 453–68.Google Scholar
Bowker, L., and Fisher, D. (2010). Computer-aided translation. In Gambier, Y. and van Doorslaer, L., eds., Handbook of Translation Studies: Volume 1. Amsterdam/Philadelphia: John Benjamins, pp. 60–5.Google Scholar
British Standards Institution. (2017). BS ISO 18587:2017 BSI Standards Publication Translation services – Post-editing of machine translation output – Requirements. London.Google Scholar
British Standards Institution. (2018). BS EN 17100:2015+A1:2017 BSI Standards Publication Translation Services – Requirements for translation services. London.Google Scholar
Catford, J. C. (1965). A Linguistic Theory of Translation: An Essay in Applied Linguistics. Oxford: Oxford University Press.Google Scholar
Christensen, T. P. (2011). Studies on the mental processes in translation memory-assisted translation: The state of the art. Trans-Kom, 4, 137–60. Available at www.trans-kom.eu/bd04nr02/trans-kom_04_02_02_Christensen_Translation_Memory.20111205.pdf.Google Scholar
Christensen, T. P., and Schjoldager, A. (2010). Translation-memory (TM) research: What do we know and how do we know it? Hermes – Journal of Language and Communication Studies, 44, 89–102.Google Scholar
Čulo, O., Gutermuth, S., Hansen-Schirra, S., and Nitzke, J. (2014). The influence of post-editing on translation strategies. In O’Brien, S., Carl, M., Simard, M., Specia, L. and Winther Balling, L., eds., Post-Editing of Machine Translation: Processes and Applications. Newcastle upon Tyne: Cambridge Scholars Publishing, pp. 200–18.Google Scholar
Daems, J., De Clercq, O., and Macken, L. (2017). Translationese and post-editese: How comparable is comparable quality? Linguistica Antverpiensia, New Series: Themes in Translation Studies, 16, 89–103. Available at https://biblio.ugent.be/publication/8516838/file/8554001.pdf.Google Scholar
De Beaugrande, R., and Dressler, W. (1981). Introduction to Text Linguistics. London/New York: Longman.Google Scholar
Doherty, S. (2017). Issues in human and automatic translation quality assessment. In Kenny, D., ed., Human Issues in Translation Technology. London/New York: Taylor and Francis, pp. 131–49.Google Scholar
Dragsted, B. (2006). Computer-aided translation as a distributed cognitive task. Pragmatics & Cognition, 14(2), 443–64. Available at https://doi.org/10.1075/pc.14.2.17dra.Google Scholar
Drugan, J. (2013). Quality in Professional Translation: Assessment and Improvement. London: Bloomsbury Academic.Google Scholar
Drugan, J., and Babych, B. (2010). Shared resources, shared values? Ethical implications of sharing translation resources. In Proceedings of the Second Joint EM+/CNGL Workshop ‘Bringing MT to the User: Research on Integrating MT in the Translation Industry’, pp. 3–9.Google Scholar
Ehrensberger-Dow, M., and Massey, G. (2017). Socio-technical issues in professional translation practice. Translation Spaces, 6(1), 104–21. Available at https://doi.org/10.1075/ts.6.1.06ehr.CrossRefGoogle Scholar
Fawcett, P. (1997). Translation and Language: Linguistic Theories Explained. Manchester: St Jerome.Google Scholar
Forcada, M. (2017). Making sense of neural machine translation. Translation Spaces, 6(2), 291–309. Available at https://doi.org/10.1075/ts.6.2.06for.Google Scholar
Garcia, I. (2007). Power shifts in web-based translation memory. Machine Translation, 21(1), 55–68. Available at https://doi.org/10.1007/s10590-008-9033-6.Google Scholar
Garcia, I. (2010). The proper place of professionals (and non-professionals and machines) in web translation. Revista Tradumàtica, 8, 1–7.Google Scholar
Garcia, I. (2011). Translating by post-editing: Is it the way forward? Machine Translation, 25(3), 217–37. Available at https://doi.org/10.1007/s10590-011-9115-8.Google Scholar
Göpferich, S., and Jääskeläinen, R. (2009). Process research into the development of translation competence: Where are we, and where do we need to go? Across Languages and Cultures, 10(2), 169–91.CrossRefGoogle Scholar
Guerberof Arenas, A. (2013). What do professional translators think about post-editing? Journal of Specialised Translation, 19, 75–95.Google Scholar
Halliday, M. (1961). Categories of the theory of grammar. Word, 17(3), 241–92.Google Scholar
Halliday, M., and Hasan, R. (1976). Cohesion in English. London: Longman.Google Scholar
Hatim, B., and Mason, I. (1990). Discourse and the Translator. London: Longman.Google Scholar
Hess, C., and Ostrom, E. (2007). Understanding Knowledge as a Commons: From Theory to Practice. Cambridge, MA: MIT Press.Google Scholar
Holmes, J. (1972). The name and nature of translation studies. In Translated: Papers on Literary Translation and Translation Studies. Amsterdam: Rodopi, pp. 66–80. Reprinted in L. Venuti, ed. (2004). The Translation Studies Reader. 2nd ed. London: Routledge, pp. 180–92.Google Scholar
Huang, H., and Wu, C. (2009). The unit of translation: Statistics speak. Meta, 54(1), 110–30. Available at https://doi.org/https://doi.org/10.7202/029796ar.Google Scholar
Jiménez-Crespo, M. A. (2017). Crowdsourcing and Online Collaborative Translations: Expanding the Limits of Translation Studies. Amsterdam: John Benjamins.Google Scholar
Kay, M. (2014). Does a computational linguist have to be a linguist? Invited Talk, COLING 2014, 25th International Conference on Computational Linguistics, Dublin, Ireland [online]. www.coling-2014.org/martin-kay.php.Google Scholar
Kenny, D. (2011). The ethics of machine translation. In New Zealand Society of Translators and Interpreters Annual Conference 2011. Auckland, New Zealand. Available at http://doras.dcu.ie/17606/.Google Scholar
Kenny, D. (2017). Introduction. In Kenny, D., ed., Human Issues in Translation Technology. London/New York: Taylor and Francis, pp. 131–49.Google Scholar
Kenny, D. (2018). Machine translation. In Rawling, P. and Wilson, P., eds., The Routledge Handbook of Translation and Philosophy. Abingdon, UK: Routledge, pp. 428–45.Google Scholar
Koponen, M. (2016). Is machine translation post-editing worth the effort? A survey of research into post-editing and effort. Journal of Specialised Translation, 25, 131–48. Available at www.jostrans.org/issue25/art_koponen.pdf.Google Scholar
Lavault-Olléon, É. (2011). L’ergonomie, nouveau paradigme pour la traductologie [Ergonomics as a New Paradigm for Translation Studies]. In ILCEA 14. Available at http://ilcea.revues.org/1078.Google Scholar
LeBlanc, M. (2017). ‘I can’t get no satisfaction!’ Should we blame translation technologies or shifting business practices? In Kenny, D., ed., Human Issues in Translation Technology. London/New York: Taylor and Francis, pp. 45–62.Google Scholar
Li, L., Nakazawa, T., and Tsuruoka, Y. (2019). Bunmyakujouhou o kouryoshita nichiei nyuuraru kikaihonyaku:文脈情報を考慮した日英ニューラル機械翻訳 [Japanese-English Neural Machine Translation in consideration of discourse information]. In 25th Natural Language Processing NLP2019 Conference Proceedings, pp. 101–4. Available at www.anlp.jp/proceedings/annual_meeting/2019/pdf_dir/A2-2.pdf.Google Scholar
Lumeras, M. A., and Way, A. (2017). On the complementarity between human translators and machine translation. Hermes, 56, 21–42. Available at https://doi.org/https://tidsskrift.dk/her/article/view/97200.Google Scholar
Massardo, I., van der Meer, J., O’Brien, S., Hollowood, F., Aranberri, N., and Drescher, K. (2016). MT Post-Editing Guidelines. Available at www.taus.net/academy/bestpractices/postedit-best-practices/machine-translation-post-editing-guidelines.Google Scholar
Moorkens, J. (2017). Under pressure: Translation in times of austerity. Perspectives, 25(3), 1–14. Available at https://doi.org/10.1080/0907676X.2017.1285331.Google Scholar
Moorkens, J., and Lewis, D. (2019). Research questions and a proposal for the future governance of translation data. Journal of Specialised Translation, 32, 2–25.Google Scholar
Moorkens, J., Toral, A., Castilho, S., and Way, A. (2018). Translators’ perceptions of literary post-editing using statistical and neural machine translation. Translation Spaces, 7(2), 240–62. Available at https://doi.org/10.1075/ts.18014.moo.Google Scholar
Nitzke, J., Hansen-Schirra, S., and Canfora, C. (2019). Risk management and post-editing competence. Journal of Specialised Translation, 31, 239–59.Google Scholar
O’Brien, S., ed. (2014). Post-Editing of Machine Translation: Processes and Applications. Newcastle upon Tyne: Cambridge Scholars Publishing. Available at http://capitadiscovery.co.uk/port/items/1216444.Google Scholar
O’Brien, S., and Simard, M., eds. (2014). Special issue: Post-Editing. Machine Translation, 28. https://link.springer.com/journal/10590/volumes-and-issues/28-3.Google Scholar
O’Hagan, M. (2013). The impact of new technologies on translation studies: A technological turn? In Millán-Varela, C. and Bartrina, F., eds., The Routledge Handbook of Translation Studies. London: Routledge, pp. 503–18.Google Scholar
Olohan, M. (2011). Translators and translation technology: The dance of agency. Translation Studies, 4(3), 342–57. Available at https://doi.org/10.1080/14781700.2011.589656.Google Scholar
Olohan, M. (2017). Technology, translation and society. Target, 29(2), 264–83. Available at https://doi.org/10.1075/target.29.2.04olo.Google Scholar
Pickering, A. (1993). The mangle of practice: Agency and emergence in the sociology of science. American Journal of Sociology, 99(3), 559–89.CrossRefGoogle Scholar
Popović, M. (2018). Error classification and analysis for machine translation quality assessment. In Moorkens, J., Castilho, S., Gaspari, F. and Doherty, S., eds., Translation Quality Assessment: From Principles to Practice. Cham, Switzerland: Springer, pp. 129–58.Google Scholar
Reiss, K., and Vermeer, H. J. (2013/1984). Towards a General Theory of Translational Action: Skopos Theory Explained. Manchester: St Jerome.Google Scholar
Risku, H., Rogl, R., and Milosevic, J. (2017). Translation practice in the field. Translation Spaces, 66(1), 3–26. Available at https://doi.org/10.1075/ts.6.1.01ris.Google Scholar
Sakamoto, A. (2019a). Unintended consequences of translation technologies: From project managers’ perspectives. Perspectives, 27(1), 58–73. Available at https://doi.org/10.1080/0907676X.2018.1473452.Google Scholar
Sakamoto, A. (2019b). Why do many translators resist post-editing? A sociological analysis using Bourdieu’ s concepts. Journal of Specialised Translation, 31, 201–16.Google Scholar
Sakamoto, A., Evans, J., and Torres-Hostench, O. (2018). Introduction to the Special Dossier Section: Translation and Disruption. Revista Tradumàtica, 16. Available at https://doi.org/https://doi.org/10.5565/rev/tradumatica.223.Google Scholar
Schaeffer, M., Nitzke, J., and Hansen-Schirra, S. (2019). Predictive turn in translation studies: Review and prospects. In Brunn, S. D. and Kehrein, R., eds., Handbook of the Changing World Language Map. Cham, Switzerland: Springer, pp. 1–23. Available at https://doi.org/10.1007/978-3-319-73400-2_217-1.Google Scholar
SDL. (2017). SDL Certification: Post-Editing Certification.Google Scholar
Shreve, G. M. (2017). Text linguistics, translating, and interpreting. In Malmkjær, K., ed., The Routledge Handbook of Translation Studies and Linguistics. London: Routledge, pp. 165–78. Available at https://doi.org/10.4324/9781315692845-12.Google Scholar
Teixeira, C. S. C., and O’Brien, S. (2017). Investigating the cognitive ergonomic aspects of translation tools in a workplace setting. Translation Spaces, 6(1), 79–103. Available at https://doi.org/10.1075/ts.6.1.05tei.Google Scholar
Toral, A. (2019). Post-editese: An exacerbated translationese. In Proceedings of MT Summit XVII, Vol. 1. Dublin, pp. 272–81.Google Scholar
Toral, A., and Way, A. (2018). What level of quality can neural machine translation attain on literary text? In Moorkens, J., Gaspari, F., Castilho, S. and Doherty, S., eds., Translation Quality Assessment: From Principles to Practice. Cham, Switzerland: Springer International, pp. 263–87. Available at https://doi.org/10.1007/978-3-319-91241-7_12.CrossRefGoogle Scholar
Vieira, L. N. (2018). Automation anxiety and translators. Translation Studies, 1–21. Available at https://doi.org/10.1080/14781700.2018.1543613.Google Scholar
Vieira, L. N., Alonso, E., and Bywood, L. (2019). Introduction: Post-editing in practice – Process, product and networks. Special issue of the Journal of Specialised Translation, 31, 2–13.Google Scholar
Wang, L. (2019). Discourse-Aware Neural Machine Translation. PhD thesis, Dublin City University.Google Scholar
Zaretskaya, A. (2017). Machine translation post-editing at TransPerfect: The ‘human’ side of the process. Revista Tradumàtica, 15, 116–23. Available at https://doi.org/https://doi.org/10.5565/rev/tradumatica.201.Google Scholar

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