1887
Volume 68, Issue 5
  • ISSN 0521-9744
  • E-ISSN: 1569-9668
USD
Buy:$35.00 + Taxes

Abstract

Abstract

Has post-editing changed the nature of translation? Are these tasks two sides of the same coin? These are some of the questions that recent developments in machine translation have brought to translation studies. The quality of the texts rendered by the new neural engines is good enough to challenge the traditional role of the human translator. Some voices even question whether there might be any place left for translators if, in the near future, their role is finally superseded by that of the post-editor. This paper offers a comprehensive view of the many aspects of post-editing with a view to shedding some light on the nature of this task. I first explore how the progress in machine translation has turned post-editing into an essential activity. Then, I present a proposal for a categorization of research areas in post-editing within the framework of translation studies. The central discussion of this paper revolves around three key ideas: (1) the conceptualization of post-editing as more than a simple, fast and inexpensive task; (2) the framing of post-editing as a dynamic process; and (3) the claim that defining quality in machine translation post-editing is not as straightforward as it may seem. The ultimate goal of this paper is to lay the foundations for further discussion into what it is that post-editing means for translation studies.

Loading

Article metrics loading...

/content/journals/10.1075/babel.00288.ric
2022-09-22
2024-09-12
Loading full text...

Full text loading...

References

  1. Allen, Jeff
    2001 “Post-editing or Not Post-editing?” International Journal for Language and Documentation81: 41–42. https://mt-archive.net/00/IJLangDoc-2001-Allen-1.pdf
    [Google Scholar]
  2. Aragonés Lumeras, Maite, and Andy Way
    2017 “On the Complementarity between Human Translators and Machine Translation.” Hermes: Journal of Language and Communication in Business561: 21–42.
    [Google Scholar]
  3. Bourdieu, Pierre
    1984Distinction: A Social Critique of the Judgement of Taste. London: Routledge
    [Google Scholar]
  4. Bowker, Lynne
    2019 “Fit-for-purpose Translation.” InThe Routledge Handbook of Translation and Technology, edited byMinako O’Hagan, 453–568. London: Routledge. 10.4324/9781315311258‑27
    https://doi.org/10.4324/9781315311258-27 [Google Scholar]
  5. Bowker, Lynne, and Jairo Buitrago Ciro
    2019Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community. Bingley, UK: Emerald Publishing Limited.
    [Google Scholar]
  6. Bundgaard, Kristine, and Tina Paulsen Christensen
    2019 “Is the Concordance Feature the New Black?: A Workplace Study of Translators’ Interaction with Translation Resources While Post-editing TM and MT Matches.” JosTrans: Journal of Specialised Translation311: 14–37.
    [Google Scholar]
  7. Canfora, Carmen, and Angelika Ottmann
    2020 “Risks in Neural Machine Translation.” Translation Spaces9 (1): 58–77. 10.1075/ts.00021.can
    https://doi.org/10.1075/ts.00021.can [Google Scholar]
  8. Carl, Michael, Barbara Dragsted, Jakob Elming, Daniel Hardt, and Arnt Lykke Jakobsen
    2011 “The Process of Post-Editing: A Pilot Study.” Copenhagen Studies in Language411: 131–142.
    [Google Scholar]
  9. Castilho, Sheila, Stephen Doherty, Federico Gaspari, and Joss Moorkens
    2018 “Approaches to Human and Machine Translation Quality Assessment.” InTranslation Quality Assessment. From Principles to Practice, edited by byJoss Moorkens, Sheila Castilho, Federico Gaspari, and Stephen Doherty, 9–38. Cham: Springer. 10.1007/978‑3‑319‑91241‑7_2
    https://doi.org/10.1007/978-3-319-91241-7_2 [Google Scholar]
  10. Castilho, Sheila, Natália Resende, and Rusland Mitkov
    2019 “What Influences the Features of Post-Editese? A Preliminary Study.” InProceedings of the 2nd Workshop on Human-Informed Translation and Interpreting Technology HiT-IT, 5–6September, Varna, Bulgaria, 19–27. Shoumen: Incoma Ltd. 10.26615/issn.2683‑0078.2019_003
    https://doi.org/10.26615/issn.2683-0078.2019_003 [Google Scholar]
  11. Christensen, Tina Paulsen, Marian Flanagan, and Anne Schjoldager
    2017 “Mapping Translation Technology Research in Translation Studies.” Hermes: Journal of Language and Communication in Business561: 7–20. 10.7146/hjlcb.v0i56.97199
    https://doi.org/10.7146/hjlcb.v0i56.97199 [Google Scholar]
  12. Cid-Leal, Pilar, María-Carmen Espín-García, and Marisa Presas
    2020 “Traducción automática y posedición: perfiles y competencias en los programas de formación de traductores” [Machine translation and post-editing: Profiles and skills in translator training programs]. MonTI: Monografías de Traducción e Interpretación [MonTI: Monographs of translation and interpretation] 111: 187–214. 10.6035/MonTI.2019.11.7
    https://doi.org/10.6035/MonTI.2019.11.7 [Google Scholar]
  13. Daems, Joke, Sonia VandepitteRobert Hartsuker, and Lieve Macken
    2015 “The Impact of Machine Translation Error Types on Post-editing Effort Indicators.” InProceedings of the 4th Workshop on Post-editing Technology and Practice, 30October–3November, Miami, USA. https://aclanthology.org/2015.mtsummit-wptp.3.pdf
    [Google Scholar]
  14. Daems, Joke, Orphee de Clercq, and Lieve Macken
    2017 “Translationese and Post-editese: How Comparable Is Comparable Quality?” Linguistica Antverpiensia161: 89–103. 10.52034/lanstts.v16i0.434
    https://doi.org/10.52034/lanstts.v16i0.434 [Google Scholar]
  15. de Almeida, Giselle
    2013 “Translating the Post-editor: An Investigation of Post-editing Changes and Correlations with Professional Experience across two Romance Languages.” Ph.D. diss., Dublin City University.
  16. de la Fuente, Rubén
    ed. 2012 “Post-editing, a Paradigm Shift?,” special issue, Revista Tradumàtica101: 147–243.
    [Google Scholar]
  17. do Carmo, Félix
    2017 “Post-editing: A Theoretical and Practical Challenge for Translation Studies and Machine Learning.” Ph.D. diss., Universida de Oporto.
  18. 2020 “‘Time Is Money’ and the Value of Translation.” Translation Spaces9 (1): 35–57. 10.1075/ts.00020.car
    https://doi.org/10.1075/ts.00020.car [Google Scholar]
  19. do Carmo, Félix, and Joss Moorkens
    2021 “Differentiating Editing, Post-editing and Revision.” InTranslation Revision and Post-editing, edited byMaarit Koponen, Brian Mossop, Isabelle Robert, Giovanna Scocchera, 35–49. London, Routledge.
    [Google Scholar]
  20. ELIS
    ELIS 2022European Language Industry Survey: Trends, Expectations, and Concerns of the European Language Industry. https://elis-survey.org/
    [Google Scholar]
  21. Flanagan, Marian, and 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 Trainer8 (2): 257–275. 10.1080/1750399X.2014.936111
    https://doi.org/10.1080/1750399X.2014.936111 [Google Scholar]
  22. Forcada, Mikel, and Felipe Sánchez-Martínez
    2015 “A General Framework for Minimizing Translation Effort: Towards a Principled Combination of Translation Technologies in Computer-aided Translation.” InProceedings of the 18th Annual Conference of the European Association for Machine Translation, 11–13May, Antalya, Turkey, edited byİlknur Durgar El-Kahlout, Mehmed Özkan, Felipe Sánchez-Martínez, Gema Ramírez-Sánchez, Fred Hollowood, and Andy Way, 27–34. https://aclanthology.org/W15-4904.pdf
    [Google Scholar]
  23. 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]
  24. García Yebra, Valentín
    1979 “¿Cicerón y Horacio preceptistas de la traducción?” [Cicero and Horace as preceptors of translation?]. Cuadernos de filología clásica [Notebooks of classical philology] 161: 139–154. revistas.ucm.es/index.php/CFCA/article/download/CFCA7980110139A/3181
    [Google Scholar]
  25. Gellerstam, Martin
    1986 “Translationese in Swedish Novels Translated from English.” InProceedings from Scandinavian Symposium on Translation Theory II, 14–15June, Lund, Sweden, 88–95. Lund: CWK Gleerup.
    [Google Scholar]
  26. Ginovart, Clara, and Antoni Oliver
    2020 “The Post-editor’s Skill Set according to Industry, Trainers and Linguists.” InMaschinelle Übersetzung für Übersetzungsprofis [Machine translation for translation professionals], edited byJörg Portsiel. Berlin: BDÜ Weiterbildungs- und Fachverlagsgesellschaft mbh. https://repositori.upf.edu/bitstream/handle/10230/46285/ginovart_bdu_posteditor.pdf?sequence=1&isAllowed=y
    [Google Scholar]
  27. Ginovart Cid, Clara, Carme Colominas, and Antoni Oliver
    2020 “Language Industry Views on the Profile of the Post-editor.” Translation Spaces9 (2): 283–313. 10.1075/ts.19010.cid
    https://doi.org/10.1075/ts.19010.cid [Google Scholar]
  28. Guerberof Arenas, Ana
    2013 “What Do Professional Translators Think about Post-editing?.” JosTrans: Journal of Specialised Translation191: 75–95.
    [Google Scholar]
  29. 2014 “Correlations between Productivity and Quality When Post-editing in a Professional Context.” Machine Translation281: 165–186. 10.1007/s10590‑014‑9155‑y
    https://doi.org/10.1007/s10590-014-9155-y [Google Scholar]
  30. Guerberof Arenas, Ana, and Joss Moorkens
    2019 “Machine Translation and Post-editing Training as Part of a Master’s Programme.” JosTrans: Journal of Specialised Translation311: 217–238.
    [Google Scholar]
  31. Hu, Ke, and Patrick Cadwell
    2016 “A Comparative Study of Post-editing Guidelines.” InProceedings of the 19th Annual Conference of the European Association for Machine Translation, in Baltic Journal of Modern Computing4 (2): 346–353. https://www.aclweb.org/anthology/W16-3420
    [Google Scholar]
  32. ISO18587
    ISO18587 2017International Standard: Translation Services – Post-editing of Machine Translation Output – Requirements.
    [Google Scholar]
  33. Kenny, Dorothy
    2018 “Sustaining Disruption?: On the Transition from Statistical to Neural Machine Translation.” Revista Tradumàtica161: 59–70. 10.5565/rev/tradumatica.221
    https://doi.org/10.5565/rev/tradumatica.221 [Google Scholar]
  34. Kenny, Dorothy, Joss Moorkens, and Félix do Carmo
    2020 “Fair MT: Towards Ethical, Sustainable Machine Translation.” Translation Spaces9 (1): 1–11. 10.1075/ts.00018.int
    https://doi.org/10.1075/ts.00018.int [Google Scholar]
  35. Koglin, Arlene, and Rossana Cuhna
    2019 “Investigating the Post-editing Effort Associated with Machine-translated Metaphors: A Process-driven Analysis.” JosTrans: Journal of Specialised Translation311: 38–59.
    [Google Scholar]
  36. Koponen, Maarit
    2016 “Is Machine Translation Post-editing Worth the Effort?: A Survey of Research into Post-editing and Effort?.” JosTrans: Journal of Specialised Translation251: 131–148.
    [Google Scholar]
  37. Koponen, Maarit, Brian Mossop, Isabelle Robert, and Giovanna Scocchera
    eds. 2021Translation Revision and Post-editing: Industry Practices and Cognitive Processes. London: Routledge. 10.4324/9781003096962
    https://doi.org/10.4324/9781003096962 [Google Scholar]
  38. Krings, Hans P.
    2001Repairing Texts: Empirical Investigations of Machine-translation Post-editing Processes, edited byGeoffrey S. Koby. Kent, OH: Kent State University Press.
    [Google Scholar]
  39. Lacruz, Isabel, and Gregory M. Shreve
    2014 “Pauses and Cognitive Effort in Post-editing.” InPost-editing of Machine Translation: Processes and Applications, edited bySharon O’Brien, Laura Winther Balling, Michael Carl, Michel Simard and Lucia Specia, 246–273. Newcastle upon Tyne: Cambridge Scholars Publishing.
    [Google Scholar]
  40. Lacruz, Isabel, Michael Carl, and Masaru Yamada
    2018 “Literality and Cognitive Effort: Japanese and Spanish.” InProceedings of Language Resources and Evaluation Conference (LREC 2018), 7–12May, Miyazaki, Japan, edited byNicoletta Calzolari, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Koiti Hasida, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis, Takenobu Tokunaga, 3818–3821. N.p.: European Language Resources Association (ELRA). https://aclanthology.org/L18-1603.pdf
    [Google Scholar]
  41. Läubli, Samuel, Rico Sennrich, and Martin Volk
    2018 “Has Machine Translation Achieved Human Parity?: A Case for Document-level Evaluation.” InProceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 31October–4November, Brussels, Belgium, 4791–4796. Stroudsburg, PA: Association for Computational Linguistics. 10.18653/v1/D18‑1512
    https://doi.org/10.18653/v1/D18-1512 [Google Scholar]
  42. Läubli, Samuel, Chantal Amrhein, Patrick Düggelin, Beatriz Gonzalez, Alena Zwahlen, and Martin Volk
    2019 “Post-editing Productivity with Neural Machine Translation: An Empirical Assessment of Speed and Quality in the Banking and Finance Domain.” InProceedings of Machine Translation Summit XVII Volume 1: Research Track, Dublin, Ireland, edited byMikel Forcada, Andy Way, Barry Haddow, Rico Sennrich, 267–272. N.p.: European Association for Machine Translation. https://aclanthology.org/W19-6626.pdf
    [Google Scholar]
  43. Mah, Seung-Hye
    2020 “Defining Language Dependent Post-editing Guidelines for Specific Content. The Case of the English–Korean Pair to Improve Literature Machine Translation Styles.” Babel66 (4–5): 811–828. 10.1075/babel.00174.mah
    https://doi.org/10.1075/babel.00174.mah [Google Scholar]
  44. Maučec, Mirjam Sepesy, and Gregor Donaj
    2020 “Machine Translation and the Evaluation of Its Quality.” InRecent Trends in Computational Intelligence, edited byAli Sadollah and Tilendra Shishir Sinha, n.p. London: IntechOpen. https://10.5772/intechopen.8906310.5772/intechopen.89063
    https://doi.org/10.5772/intechopen.89063 [Google Scholar]
  45. Mesa-Lao, Bartolomé
    2013Introduction to Post-editing. The CasMaCat GUI. SEECAT project. Center for Research and Innovation in Translation and Translation Technology. Copenhagen Business School, Denmark. https://bridge.cbs.dk/projects/seecat/material/hand-out_post-editing_bmesa-lao.pdf
    [Google Scholar]
  46. Moorkens, Joss, Sharon O’Brien, Igor A. L. da Silva, Norma B. de Lima Fonseca, and Fabio Alves
    2015 “Correlations of Perceived Post-editing Effort with Measurements of Actual Effort.” Machine Translation291: 267–284. 10.1007/s10590‑015‑9175‑2
    https://doi.org/10.1007/s10590-015-9175-2 [Google Scholar]
  47. Moorkens, Joss, and Sharon O’Brien
    2017 “Assessing User Interface Needs of Post-Editors of Machine Translation.” InHuman Issues in Translation Technology, edited byDorothy Kenny, 109–130. London and New York: Routledge.
    [Google Scholar]
  48. Moorkens, Joss, Sheila Castilho, Federico Gaspari, and Stephen Doherty
    eds. 2018aTranslation Quality Assessment: From Principles to Practice. Cham: Springer. 10.1007/978‑3‑319‑91241‑7
    https://doi.org/10.1007/978-3-319-91241-7 [Google Scholar]
  49. Moorkens, Joss, Antonio Toral, Sheila Castilho, and Andy Way
    2018b “Translators’ Perceptions of Literary Post-editing Using Statistical and Neural Machine Translation.” Translation Spaces7 (2): 240–262. 10.1075/ts.18014.moo
    https://doi.org/10.1075/ts.18014.moo [Google Scholar]
  50. Moorkens, Joss
    2020 “A Tiny Cog in a Large Machine: Digital Taylorism in the Translation Industry.” Translation Spaces9 (1): 12–34. 10.1075/ts.00019.moo
    https://doi.org/10.1075/ts.00019.moo [Google Scholar]
  51. Hadley, James, Maja Popović, Haithem Afli, Andy Way
    eds. 2019In Proceedings of the Qualities of Literary Machine Translation. Machine Translation Summit2019, 19 August, Dublin, Ireland. N.p.: European Association for Machine Translation. https://aclanthology.org/W19-73.pdf
    [Google Scholar]
  52. National Research Council
    National Research Council 1966Language and Machines: Computers in Translation and Linguistics. Washington, DC: The National Academies Press. 10.17226/9547
    https://doi.org/10.17226/9547 [Google Scholar]
  53. Nayek, Tapas, Sudip Kumar Naskar, Santanu Pal, Marcos Zampieri, Mihaela Vela, Josef van Genabith
    2015 “CATaLog: New Approaches to TM and Post Editing Interfaces.” InProceedings of the Workshop on Natural Language Processing for Translation Memories (NLP4TM), Hissar, Bulgaria, 36–42, Constantin Orasan, Rohit Gupta. N.p.: Association for Computational Linguistics. https://aclanthology.org/W15-5206.pdf
    [Google Scholar]
  54. Nitzke, Jean
    2019Problem Solving Activities in Post-editing and Translation from Scratch: A Multi-method Study. Berlin: Language Science Press.
    [Google Scholar]
  55. Nord, Christiane
    1997Translating as a Purposeful Activity. Manchester: St. Jerome.
    [Google Scholar]
  56. O’Brien, Sharon
    2002 “Teaching Post-editing: A Proposal for Course Content.” InProceedings of the 6th EAMT Workshop: Teaching Machine Translation, 14–15November, Manchester, UK. N.p.: European Association for Machine Translation. https://aclanthology.org/2002.eamt-1.11.pdf
    [Google Scholar]
  57. 2005 “Methodologies for Measuring the Correlations between Post-editing Effort and Machine Translatability.” Machine Translation19 (1): 37–58. 10.1007/s10590‑005‑2467‑1
    https://doi.org/10.1007/s10590-005-2467-1 [Google Scholar]
  58. 2006 “Pauses as Indicators of Cognitive Effort in Post-editing Machine Translation Output.” Across Languages and Cultures7 (1): 1–21. 10.1556/Acr.7.2006.1.1
    https://doi.org/10.1556/Acr.7.2006.1.1 [Google Scholar]
  59. 2007 “An Empirical Investigation of Temporal and Technical Post-editing Effort.” Translation and Interpreting Studies: The Journal of the American Translation and Interpreting Studies Association2 (1): 83–136. 10.1075/tis.2.1.03ob
    https://doi.org/10.1075/tis.2.1.03ob [Google Scholar]
  60. 2011 “Towards Predicting Post-editing Productivity.” Machine Translation25 (3): 197–215. 10.1007/s10590‑011‑9096‑7
    https://doi.org/10.1007/s10590-011-9096-7 [Google Scholar]
  61. O’Brien, Sharon, and Joss Moorkens
    2014 “Towards Intelligent Post-editing Interfaces.” InProceedings of the FIT 20th World Congress, 4–6August, Berlin Germany.
    [Google Scholar]
  62. O’Brien, Sharon, and Michel Simard
    2014 “Post-editing,” special issue, Machine Translation28 (3–4): 159–339. 10.1007/s10590‑014‑9166‑8
    https://doi.org/10.1007/s10590-014-9166-8 [Google Scholar]
  63. O’Brien, Sharon, Laura Winther Balling, Michael Carl, Michel Simard, and Lucia Specia
    2014Post-editing of Machine Translation: Processes and Applications. Newcastle upon Tyne: Cambridge Scholars Publishing.
    [Google Scholar]
  64. O’Brien, Sharon, Maureen Ehrensberger-Dow, Marcel Hasler, and Megan Connolly
    2017 “Irritating CAT Tool Features that Matter to Translators.” Hermes: Journal of Language and Communication in Business561: 145–162.
    [Google Scholar]
  65. O’Brien, Sharon, and Owen Conlan
    2019 “Moving towards Personalising Translation Technology.” InMoving Boundaries in Translation Studies, Helle V. Dam, Matilde Nisbeth Brøgger, Karen Korning Zethsen, 81–97. London: Routledge.
    [Google Scholar]
  66. O’Brien, Sharon, and Maureen Ehrensberger-Dow
    2020 “MT Literacy: A Cognitive View.” Translation, Cognition and Behavior3 (2): 145–164. 10.1075/tcb.00038.obr
    https://doi.org/10.1075/tcb.00038.obr [Google Scholar]
  67. O’Brien, Sharon
    2021 “Post-editing: Is That Even the Right Word for the Future?.” Speech delivered atDGT-Vilnius University, 5 March 2021. 10.1075/hts.5.pos3
    https://doi.org/10.1075/hts.5.pos3 [Google Scholar]
  68. Parra Escartín, Carla, and Helena Moniz
    2019 “Ethical Considerations on the Use of Machine Translation and Crowdsourcing in Cascading Crises.” InTranslation in Cascading Crisis, edited byFederico M. Federici and Sharon O’Brien, 132–151. London: Routledge. 10.4324/9780429341052‑7
    https://doi.org/10.4324/9780429341052-7 [Google Scholar]
  69. Pérez Macías, Lorena
    2020 “What Do Translators Think About Post-Editing?: A Mixed-Methods Study of Translators’ Fears, Worries and Preferences on Machine Translation Post-Editing.” Revista Tradumàtica181: 11–32. 10.5565/rev/tradumatica.227
    https://doi.org/10.5565/rev/tradumatica.227 [Google Scholar]
  70. Plaza-Lara, Cristina
    2019 “Análisis DAFO sobre la inclusión de la traducción automática y la posedición en los másteres de la red EMT.” JosTrans: Journal of Specialised Translation311: 260–280.
    [Google Scholar]
  71. 2020 “How Does Machine Translation and Post-editing Affect Project Management?: An Interdisciplinary Approach.” Hikma19 (2): 163–182. 10.21071/hikma.v19i2.12516
    https://doi.org/10.21071/hikma.v19i2.12516 [Google Scholar]
  72. Pym, Anthony, and Esther Torres-Simón
    2021 “Efectos de la automatización en las competencias básicas del traductor: la traducción automática neuronal” [Effects of automation on the translator’s core competencies: Neural machine translation]. InOcupaciones y lenguaje: Indicadores y análisis de competencias lingüísticas en el ámbito laboral [Language professionals: Indicators and analysis of language competences in the workplace], edited byAntoni Vidal Suñe and Amado Alarcón, 475–506. Tarragona: Universitat Rovira i Virgili.
    [Google Scholar]
  73. Rico, Celia
    2012 “A Flexible Decision Tool for Implementing Post-editing Guidelines.” Localisation Focus11 (1): 54–66.
    [Google Scholar]
  74. 2017 “La formación de traductores en traducción automática” [Training translators in machine translation]. Revista Tradumàtica151: 75–96. 10.5565/rev/tradumatica.200
    https://doi.org/10.5565/rev/tradumatica.200 [Google Scholar]
  75. Rico, Celia, and M. Ariano
    2014 “Defining Language Dependent Post-editing Rules: The Case of the Language Pair English-Spanish.” InPost-editing of Machine Translation: Processes and Applications, edited bySharon O’Brien, Laura Winther Balling, Michael Carl, Michel Simard and Lucia Specia, 299–322. Newcastle upon Tyne: Cambridge Scholars Publishing.
    [Google Scholar]
  76. Rico, Celia, and Enrique Torrejón
    2012 “Skills and Profile of the New Role of the Translator as MT Post-editor.” Revista Tradumàtica101: 166–178. 10.5565/rev/tradumatica.18
    https://doi.org/10.5565/rev/tradumatica.18 [Google Scholar]
  77. Risku, Hanna
    2010 “A Cognitive Scientific View on Technical Communication and Translation: Do Embodiment and Situatedness Really Make a Difference?” Target: International Journal of Translation Studies22 (1): 94–111. 10.1075/target.22.1.06ris
    https://doi.org/10.1075/target.22.1.06ris [Google Scholar]
  78. Rozmyslowicz, Tomasz
    2014 “Machine Translation: A Problem for Translation Theory.” New Voices in Translation Studies111: 145–163. www.iatis.org/images/stories/publications/new-voices/Issue11-2014/articles/06-abstract-Rozmyslowicz-2014.pdf
    [Google Scholar]
  79. Sakamoto, Akiko
    2019 “Why Do Many Translators Resist Post-editing?: A Sociological Analysis Using Bourdieu’s Concepts.” JosTrans: Journal of Specialised Translation311: 201–216.
    [Google Scholar]
  80. Sakamoto, Akiko, and Masura Yamada
    2020 “Social Groups in Machine Translation Post-editing: A SCOT Analysis.” Translation Spaces9 (1): 78–97. 10.1075/ts.00022.sak
    https://doi.org/10.1075/ts.00022.sak [Google Scholar]
  81. Sakamoto, Akiko, Jonathan Evans, and Olga Torres Hostench
    2018 “Translation and Disruption.” Revista Tradumàtica161: 52–58.
    [Google Scholar]
  82. Sánchez-Gijón, Pilar
    2016 “La posedición: hacia una definición competencial del perfil y una descripción multidimensional del fenómeno” [Post-editing: Towards a competency-based definition of the profile and a multidimensional description of the phenomenon]. Sendebar: Revista de Traducción e Interpretación [Sendebar: Journal of translation and interpreting] 271: 151–162.
    [Google Scholar]
  83. Sánchez-Gijón, Pilar, and R. Piqué Huerta, R.
    2020 “Conseqüències de la traducció automàtica neuronal sobre les llengües d’arribada” [Consequences of neural machine translation on target languages]. Revista Tradumàtica181: 1–10. 10.5565/rev/tradumatica.277
    https://doi.org/10.5565/rev/tradumatica.277 [Google Scholar]
  84. Screen, Ben
    2019 “What Effect Does Post-editing Have on the Translation Product from an End-user’s Perspective?” JosTrans: Journal of Specialised Translation311: 133–157.
    [Google Scholar]
  85. Silva, Roberto
    2014 “Integrating Post-Editing MT in a Professional Translation Workflow.” InPost-editing of Machine Translation: Processes and Applications, edited bySharon O’Brien, Laura Winther Balling, Michael Carl, Michel Simard and Lucia Specia, 24–50. Newcastle upon Tyne: Cambridge Scholars Publishing
    [Google Scholar]
  86. Simianer, Patrick, Sariya Karimova, and Stefan Riezler
    2004 “A Post-editing Interface for Immediate Adaptation in Statistical Machine Translation.” InProceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, 11–16December, Osaka, Japan, 16–20. https://aclanthology.org/C16-2.pdf
    [Google Scholar]
  87. Toral, Antonio
    2019 “Post-editese: An Exacerbated Translationese.” InProceedings of Machine Translation Summit XVII Volume 1: Research Track, 19–23August, Dublin Ireland, editedMikel Forcada, Andy Way, Barry Haddow, and Rico Sennrich, 273–281. N.p.: European Association for Machine Translation. https://aclanthology.org/W19-66.pdf
    [Google Scholar]
  88. 2020 “Reassessing Claims of Human Parity and Super-Human Performance in Machine Translation.” In22nd Annual Conference of the European Association for Machine Translation EAMT, 3–5November, Lisboa, Portugal, edited byAndré Martins , 185–194. N.p.: European Association for Machine Translation. https://aclanthology.org/2020.eamt-1.20.pdf
    [Google Scholar]
  89. Toral, Antonio, and Andy Way
    2015 “Machine-assisted Translation of Literary Text: A Case Study.” Translation Spaces4 (2): 240–267. 10.1075/ts.4.2.04tor
    https://doi.org/10.1075/ts.4.2.04tor [Google Scholar]
  90. Toral, Antonio, Martijn Wieling and Andy Way
    2018 “Post-editing Effort of a Novel with Statistical and Neural Machine Translation.” Frontiers in Digital Humanities151. 10.3389/fdigh.2018.00009
    https://doi.org/10.3389/fdigh.2018.00009 [Google Scholar]
  91. Torrejón Díaz, Enrique, and Celia Rico
    2002 “Controlled Translation: A New Teaching Scenario Tailor-made for the Translation Industry.” InProceedings of the 6th EAMT Workshop: Teaching Machine Translation, 14–15November, Manchester UK, 107–116. N.p.: European Association for Machine Translation. https://aclanthology.org/2004.tc-1.4.pdf
    [Google Scholar]
  92. Torres-Hostench, Olga, Marisa Presas, and Pilar Cid-Leal
    2016El uso de traducción automática y posedición en las empresas de servicios lingüísticos españolas: Informe de investigación ProjecTA 2015 [The use of machine translation and post-editing in Spanish language service companies: ProjecTA research report 2015]. Bellaterra. https://ddd.uab.cat/record/148361
    [Google Scholar]
  93. Vasconcellos, Muriel, and Marjorie León
    1987 “SPANAM and ENGSPAN: Machine Translation in a Combined Language Service at the Pan American Health Organization.” InMachine Translation Systems: Survey and Selected Papers, edited byJonathan Slocum, 187–235. London and New York: Cambridge University Press.
    [Google Scholar]
  94. Vieira, Lucas Nunes
    2019 “Post-editing of Machine Translation.” InThe Routledge Handbook of Translation and Technology, edited byMinako O’Hagan, 319–336. London: Routledge. 10.4324/9781315311258‑19
    https://doi.org/10.4324/9781315311258-19 [Google Scholar]
  95. Vieira, Lucas Nunes, Elisa Alonso, and Lindsay Bywood
    2019 “Post-editing in Practice: Process, product and networks.” JosTrans: Journal of Specialised Translation311: 2–13.
    [Google Scholar]
  96. Voigt, Rob, and Dan Jurafsky
    2012 “Towards a Literary Machine Translation: The Role of Referential Cohesion.” InProceedings of the NAACL-HLT 2012 Workshop on Computational Linguistics for Literature, 8June, Montréal, Canada, edited byDavid Elson, Anna Kazantseva, Rada Mihalcea, and Stan Szpakowicz, 18–25. Stroudsburg PA: Association for Computational Linguistics. https://aclanthology.org/W12-2503
    [Google Scholar]
  97. Way, Andy
    2013 “Traditional and Emerging Use-cases for Machine Translation.” InProceedings of Translating and the Computer351, 28–29November, London UK. https://aclanthology.org/2013.tc-1.12.pdf
    [Google Scholar]
  98. Weaver, Weaver
    1955 “Translation.” InMachine Translation of Languages: Fourteen Essays, edited byWilliam N. Locke and Andrew Donald Booth, 15–23. Cambridge, MA: MIT Press.
    [Google Scholar]
  99. Zaretskaya, Anna, Mihaela Vela, Gloria Corpas Pastor, and Miriam Seghiri
    2016 “Measuring Post-editing Time and Effort for Different Types of Machine Translation Errors.” New Voices in Translation Studies15 (15): 63–91.
    [Google Scholar]
/content/journals/10.1075/babel.00288.ric
Loading
/content/journals/10.1075/babel.00288.ric
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error