1887
Volume 69, Issue 5
  • ISSN 0521-9744
  • E-ISSN: 1569-9668
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Abstract

Abstract

With increasing acknowledgment of enhanced quality now achievable by Machine Translation, new possibilities have emerged through collaboration between human and machine in the translation process, including providing varying qualities of translation in response to quality/efficiency requirements. This paper presents surveys of post-graduate students of translation conducted over four consecutive years to examine if their awareness and preparedness have kept pace with these possibilities. It is found that respondents across the years generally perceive their awareness as lacking, are hesitant in employing MT, and show marked reservations when reconsidering issues such as quality and the preeminent position of the human translator. A review of existing research in translator training points towards a lopsided emphasis on linguistic competence and standalone courses for introducing technology as the primary cause behind low adoption. The need of the hour is translator training that fully integrates technology in the translation process and also provides a clear framework to adjust quality/efficiency is important to ensure preparedness. A repeat survey of students from 2021 who were trained under this model shows an increase in willingness to use MT and to consider quality as dependent on intended use. The focus here is on Chinese-English translation, but the discussion may find resonance with other language pairs.

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2023-09-22
2024-09-15
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References

  1. Allen, Jeffrey
    2003 “Post-Editing.” InComputers and Translation: A Translator’s Guide, edited byHarold Somers, 297–317. Benjamins Translation Library 35. Amsterdam: John Benjamins. 10.1075/btl.35.19all
    https://doi.org/10.1075/btl.35.19all [Google Scholar]
  2. Bittner, Hansjörg
    2020Evaluating the Evaluator: A Novel Perspective on Translation Quality Assessment. New York: Routledge.
    [Google Scholar]
  3. Bowker, Lynne
    2005 “What Does It Take to Work in the Translation Profession in Canada in the 21st Century?: Exploring a Database of Job Advertisements.” Meta49 (4): 960–972. 10.7202/009804ar
    https://doi.org/10.7202/009804ar [Google Scholar]
  4. Bowker, Lynne, and Jairo Buitrago Ciro
    2019Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community. Bingley: Emerald Publishing.
    [Google Scholar]
  5. Buysschaert, Joost, María Fernández-Parra, Koen Kerremans, Maarit Koponen, and Gys-Walt Van Egdom
    2018 “Embracing Digital Disruption in Translator Training: Technology Immersion in Simulated Translation Bureaus.” Tradumàtica: Tecnologies de La Traducció161 (December): 125. 10.5565/rev/tradumatica.209
    https://doi.org/10.5565/rev/tradumatica.209 [Google Scholar]
  6. Chang, Daphne Qi-rong, Samuel Ju-hsin Yang, and Tracy Jr-yun Wang
    2019 “Dongji! Wo xuyao dongji! Ronghe diannao fuzhu fanyi de daxue fanyi ke” 動機!我需要動機!融合電腦輔助翻譯的大學翻譯課 [Motivation! I need motivation! Incorporation of CAT into university translation courses]. Fanyixue yanjiu jikan翻譯學研究集刊 [Studies of translation and interpretation] 231 (November): 129–156.
    [Google Scholar]
  7. Chung, Eun Seon
    2020 “The Effect of L2 Proficiency on Post-Editing Machine Translated Texts.” The Journal of AsiaTEFL17 (1): 182–193. 10.18823/asiatefl.2020.17.1.11.182
    https://doi.org/10.18823/asiatefl.2020.17.1.11.182 [Google Scholar]
  8. Cui, Qiliang 崔启亮
    2014 “Lun jiqi fanyi de yihou bianji”论机器翻译的译后编辑 [On post-editing of machine translation].” Zhongguo fanyi中国翻译 [Chinese translators journal] (6): 68–73.
    [Google Scholar]
  9. Cui, Qiliang
    2019a “MTI Programs: Employment Investigation.” InRestructuring Translation Education: Implications from China for the Rest of the World, edited byFeng Yue , 55–68. Singapore: Springer Singapore. 10.1007/978‑981‑13‑3167‑1_5
    https://doi.org/10.1007/978-981-13-3167-1_5 [Google Scholar]
  10. 2019b “MTI Programs: Teaching and Learning.” InRestructuring Translation Education: Implications from China for the Rest of the World, edited byFeng Yue , 41–54. Singapore: Springer Singapore. 10.1007/978‑981‑13‑3167‑1_4
    https://doi.org/10.1007/978-981-13-3167-1_4 [Google Scholar]
  11. Doherty, Stephen
    2016 “The Impact of Translation Technologies on the Process and Product of Translation.” International Journal of Communication101 (February): 969.
    [Google Scholar]
  12. Drugan, Joanna
    2013Quality in Professional Translation: Assessment and Improvement. London and New York: Bloomsbury.
    [Google Scholar]
  13. “EMT Competence Framework 2017” 2017 European Master’s in Translation (EMT) 2017 https://ec.europa.eu/info/sites/default/files/emt_competence_fwk_2017_en_web.pdf
  14. “EMT Competence Framework 2022” 2022 European Master’s in Translation (EMT) 2022 https://commission.europa.eu/document/download/b482a2c0-42df-4291-8bf8-923922ddc6e1_en?filename=emt_competence_fwk_2022_en.pdf
  15. Escartín, Carla Parra, and Marie-Josée Goulet
    2020 “When the Post-Editor Is Not a Translator.” InTranslation Revision and Post-Editing, edited byMaarit Koponen, Brian Mossop, Isabelle S. Robert, and Giovanna Scocchera, 89–106. London and New York : Rutledge 2020.: Routledge. 10.4324/9781003096962‑8
    https://doi.org/10.4324/9781003096962-8 [Google Scholar]
  16. Garcia, Ignacio
    2011 “Translating by Post-Editing: Is It the Way Forward?” Machine Translation25 (3): 217–237. 10.1007/s10590‑011‑9115‑8
    https://doi.org/10.1007/s10590-011-9115-8 [Google Scholar]
  17. Gaspari, Federico, Hala Almaghout, and Stephen Doherty
    2015 “A Survey of Machine Translation Competences: Insights for Translation Technology Educators and Practitioners.” Perspectives23 (3): 333–358. 10.1080/0907676X.2014.979842
    https://doi.org/10.1080/0907676X.2014.979842 [Google Scholar]
  18. Grace, Katja, John Salvatier, Allan Dafoe, Baobao Zhang, and Owain Evans
    2018 “When Will AI Exceed Human Performance? Evidence from AI Experts.” ArXiv:1705.08807 [Cs], May. arxiv.org/abs/1705.0880710.1613/jair.1.11222
    https://doi.org/10.1613/jair.1.11222 [Google Scholar]
  19. Hassan, Hany, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang,
    2018 “Achieving Human Parity on Automatic Chinese to English News Translation.” CitetononCRdoi:10.48550/ARXIV.1803.05567
    https://doi.org/Cite to nonCR doi: 10.48550/ARXIV.1803.05567 [Google Scholar]
  20. Hutchins, William John, and Harold L. Somers
    1997An Introduction to Machine Translation. 21. printing. London: Academic Press.
    [Google Scholar]
  21. “ISO 18587:2017 Translation Services – Post-Editing of Machine Translation Output – Requirements” 2017 International Organization for Standardization 2017 https://www.iso.org/standard/62970.html
  22. Jia, Yanfang, Michael Carl, and Xiangling Wang
    2019 “Post-Editing Neural Machine Translation versus Phrase-Based Machine Translation for English-Chinese.” Machine Translation33 (1–2): 9–29. 10.1007/s10590‑019‑09229‑6
    https://doi.org/10.1007/s10590-019-09229-6 [Google Scholar]
  23. Kenny, Dorothy, and Stephen Doherty
    2014 “Statistical Machine Translation in the Translation Curriculum: Overcoming Obstacles and Empowering Translators.” The Interpreter and Translator Trainer8 (2): 276–94. 10.1080/1750399X.2014.936112
    https://doi.org/10.1080/1750399X.2014.936112 [Google Scholar]
  24. Killman, Jeffrey
    2018 “A Context-Based Approach to Introducing Translation Memory in Translator Training.” InTranslation, Globalization and Translocation, edited byConcepción B. Godev, 137–159. Cham: Springer International Publishing. 10.1007/978‑3‑319‑61818‑0_8
    https://doi.org/10.1007/978-3-319-61818-0_8 [Google Scholar]
  25. Konttinen, Kalle, Leena Salmi, and Maarit Koponen
    2020 “Revision and Post-Editing Competences in Translator Education.” InTranslation Revision and Post-Editing, edited byMaarit Koponen, Brian Mossop, Isabelle S. Robert, and Giovanna Scocchera, 187–202. London and New York: Rutledge. 10.4324/9781003096962‑15
    https://doi.org/10.4324/9781003096962-15 [Google Scholar]
  26. Kornacki, Michał
    2018Computer-Assisted Translation (CAT) Tools in the Translator Training Process. Berlin and New York: Peter Lang GmbH, Internationaler Verlag der Wissenschaften. 10.3726/b14783
    https://doi.org/10.3726/b14783 [Google Scholar]
  27. Läubli, Samuel, Rico Sennrich, and Martin Volk
    2018 “Has Machine Translation Achieved Human Parity? A Case for Document-Level Evaluation.” ArXiv:1808.07048 [Cs], August. arxiv.org/abs/1808.0704810.18653/v1/D18‑1512
    https://doi.org/10.18653/v1/D18-1512 [Google Scholar]
  28. Man, Deliang, Aiping Mo, Meng Huat Chau, John Mitchell O’Toole, and Charity Lee
    2020 “Translation Technology Adoption: Evidence from a Postgraduate Programme for Student Translators in China.” Perspectives28 (2): 253–270. 10.1080/0907676X.2019.1677730
    https://doi.org/10.1080/0907676X.2019.1677730 [Google Scholar]
  29. Massardier-Kenney, Françoise
    2017 “An MA in Translation.” InTeaching Translation: Programs, Courses, Pedagogies, edited byLawrence Venuti, 32–38. London and New York: Routledge.
    [Google Scholar]
  30. Massardo, Isabella, Jap van der Meer, Sharon O’Brian, Fred Hollowood, Nora Aranberri, and Katrin Drescher [Google Scholar]
  31. Massey, Gary, and Maureen Ehrensberger-Dow
    2017 “Machine Learning: Implications for Translator Education.” Lebende Sprachen62 (2): 300–312. 10.1515/les‑2017‑0021
    https://doi.org/10.1515/les-2017-0021 [Google Scholar]
  32. Mellinger, Christopher D.
    2017 “Translators and Machine Translation: Knowledge and Skills Gaps in Translator Pedagogy.” The Interpreter and Translator Trainer11 (4): 280–93. 10.1080/1750399X.2017.1359760
    https://doi.org/10.1080/1750399X.2017.1359760 [Google Scholar]
  33. 2018 “Problem-Based Learning in Computer-Assisted Translation Pedagogy.” HERMES – Journal of Language and Communication in Business, no.57 (June): 195–208. 10.7146/hjlcb.v0i57.106205
    https://doi.org/10.7146/hjlcb.v0i57.106205 [Google Scholar]
  34. Pym, Anthony
    2012On Translator Ethics: Principles for mediation between cultures. Benjamins Translation Library, v. 1041. Amsterdam: John Benjamins. 10.1075/btl.104
    https://doi.org/10.1075/btl.104 [Google Scholar]
  35. Qin, Ying 秦颖
    2018 “Jiyu shenjing wangluo de jiqi fanyi zhiliang pingxi ji dui fanyi jiaoxue deyingxiang”基于神经网络的机器翻译质量评析及对翻译教学的影响 [An analytical study of neural network machine translation and its impacts on translation teaching].” Waiyu dianhua jiaoxue外语电化教学 [Translation teaching and research] 1801 (April): 51–56.
    [Google Scholar]
  36. Qu, Shaobing
    2020 Zhongguo yuyan fuwu fazhan baogao (2020)中国语言服务发展报告(2020) [Language service development in China 2020]. Beijing: Shangwu yinshu guan.
    [Google Scholar]
  37. Rodríguez de Céspedes, Begoña
    2019 “Translator Education at a Crossroads:The Impact of Automation.” Lebende Sprachen64 (1): 103–121. 10.1515/les‑2019‑0005
    https://doi.org/10.1515/les-2019-0005 [Google Scholar]
  38. Sarti, Gabriele, Arianna Bisazza, Ana Guerberof Arenas, and Antonio Toral
    2022 “DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages.” InProceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 7795-7816. Abu Dhabi, United Arab Emirates: Association for Computational Linguistics. 10.18653/v1/2022.emnlp‑main.532
    https://doi.org/10.18653/v1/2022.emnlp-main.532 [Google Scholar]
  39. Somers, Harold
    ed. 2003Computers and Translation: A Translator’s Guide. Amsterdam: John Benjamins. 10.1075/btl.35
    https://doi.org/10.1075/btl.35 [Google Scholar]
  40. Van Wyke, Ben
    2017 “An Undergraduate Certificate in Translation Studies.” InTeaching Translation: Programs, Courses, Pedagogies, edited byLawrence Venuti, 17–24. London and New York: Routledge.
    [Google Scholar]
  41. Venkatesan, Hari
    2009 “Teaching Translation Memory Systems: SDL Trados 2007.” Journal of Translation Studies13 (1–2): 71–81.
    [Google Scholar]
  42. 2021 “The Fourth Dimension in Translation: Time and Disposability.” Perspectives30 (4): 662–677. 10.1080/0907676X.2021.1939739
    https://doi.org/10.1080/0907676X.2021.1939739 [Google Scholar]
  43. Von Flotow, Luise
    2017 “A Doctoral Program in Translation Studies.” InTeaching Translation: Programs, Courses, Pedagogies, edited byLawrence Venuti, 46–52. London and New York: Routledge.
    [Google Scholar]
  44. Wang, Huashu 王华树
    2013 “Yuyan fuwu hangye jishu shiyuxia de MTI jishu kecheng tixi goujian”语言服务行业技术视域下的MTI技术课程体系构建 [A constructive technology curriculum for MTI education from the perspective of language service industry technologies]. Zhongguo fanyi中国翻译 [Chinese translator’s journal] (6): 23–28.
    [Google Scholar]
  45. Wang, Xiangling, Tingting Wang, Ricardo Muñoz Martín, and Yanfang Jia
    2021 “Investigating Usability in Postediting Neural Machine Translation: Evidence from Translation Trainees’ Self-Perception and Performance:” Across Languages and Cultures22 (1): 100–123. 10.1556/084.2021.00006
    https://doi.org/10.1556/084.2021.00006 [Google Scholar]
  46. Way, Andy
    2018 “Quality Expectations of Machine Translation.” InTranslation Quality Assessment, edited byJoss Moorkens, Sheila Castilho, Federico Gaspari, and Stephen Doherty, 11:159–78. Machine Translation: Technologies and Applications. Cham: Springer International Publishing. 10.1007/978‑3‑319‑91241‑7_8
    https://doi.org/10.1007/978-3-319-91241-7_8 [Google Scholar]
  47. Wu, Di, Lawrence Jun Zhang, and Lan Wei
    2019 “Developing Translator Competence: Understanding Trainers’ Beliefs and Training Practices.” The Interpreter and Translator Trainer13 (3): 233–54. 10.1080/1750399X.2019.1656406
    https://doi.org/10.1080/1750399X.2019.1656406 [Google Scholar]
  48. Wu, Yonghui,
    2016 “Google’s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.” ArXiv:1609.08144 [Cs], October. arxiv.org/abs/1609.08144
    [Google Scholar]
  49. Xu, Mianjun, and Xiaoye You
    2021 “Translation Practice of Master of Translation and Interpreting (MTI) Teachers in China: An Interview-Based Study.” The Interpreter and Translator Trainer15 (3): 343–59. 10.1080/1750399X.2021.1900711
    https://doi.org/10.1080/1750399X.2021.1900711 [Google Scholar]
  50. Zhang, Xiaochun, and Lucas Nunes Vieira
    2021 “CAT Teaching Practices: An International Survey.” JoSTrans: The Journal of Specialised Translation361: 99–142.
    [Google Scholar]
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