Cover not available

In:Psycholinguistic and Cognitive Inquiries into Translation and Interpreting
Edited by Aline Ferreira and John W. Schwieter
[Benjamins Translation Library 115] 2015
► pp. 145–174

Get fulltext from our e-platform
JBE logo with link
PDF logo with download linkDownload Book PDF
authorization required

Post-editing machine translation

A usability test for professional translation settings

ORCiD logo with link | Copenhagen Business School
 | Johannes Gutenberg-Universität Mainz
 | Johannes Gutenberg-Universität Mainz
Published online: 22 January 2015
DOI logo with link
https://doi.org/10.1075/btl.115.07car
Traditionally, the quality of machine translation (MT) output at best was sufficient to serve as an informative translation for users without any knowledge of the source language but not for the purpose of professional translation. However, still restricted to limited scenarios dependent on language pair and text type, MT quality has improved in such a way that it has found its way into professional translation workflows–especially when software localization and technical documentation are concerned. With this development in mind, the research questions of our study focus on the empirical investigation of the efficiency of post-editing and on typical revision strategies and processes. We present an empirical comparison of three translation tasks using Translog-II and Tobii eyetracking, in which 24 translators translate 6 English texts into German: two of the texts were translated from scratch, two other texts were pre-translated with Google MT, which the translator then had to post-edit and in a third task, two Google pre-translated texts had to be post-edited without the translator being able to consult the source text. We use keylogging, eyetracking and retrospective interviews to track back the different (un)conscious cognitive processes and problems involved in the different tasks. On the basis of this multi-method approach, we compare post-editing strategies to translation strategies. Furthermore, processing time as well as cognitive efforts during translations are contrasted and discussed.
References (53)
Adriaens, Geert, Roger Havenith, Rick Wocjik, and Bruno Tersago. 1996. First International Workshop on Controlled Language Applications. CLAW 1996 , Leuven, Belgium.
Adriaens, Geert, Jeffrey Allen, Arendse Bernth, Kurt Godden, Teruko Mitamura, Eric Nyberg, Rick Wocjik, and Rémi Zajac. 2000. Third International Workshop on Controlled Language Applications. CLAW 2000 , Seattle, Washington.
Aymerich, Julia. 2005. Using Machine Translation for Fast, Inexpensive, and Accurate Health Information Assimilation and Dissemination: Experiences at the Pan American Health Organization. Salvador – Bahia, Brazil: 9th World Congress on Health Information and Libraries. Accessed from: [URL], March 13, 2013.Google Scholar logo with link to Google Scholar
Aziz, Wilker, Sheila C.M. Sousa, and Lucia Specia. 2012. “PET: A Tool for Post-editing and Assessing Machine Translation.” Presented at the Eighth International Conference on Language Resources and Evaluation , Istanbul, Turkey.
Carl, Michael. 2012a. “Translog-II: A Program for Recording User Activity Data for Empirical Translation Process Research.” Presented at the Eighth International Conference on Language Resources and Evaluation , Istanbul, Turkey.
. 2012b. “The CRITT TPR-DB 1.0: A Database for Empirical Human Translation Process Research.” In Proceedings of the AMTA 2012 Workshop on Post-Editing Technology and Practice (WPTP 2012), ed. by Sharon O’Brien, Michel Simard, and Lucia Specia, 9–18. Stroudsburg, PA: Association for Machine Translation in the Americas (AMTA).Google Scholar logo with link to Google Scholar
Carl, Michael, and Martin Kay. 2011. “Gazing and Typing Activities during Translation: A Comparative Study of Translation Units of Professional and Student Translators.” Meta 56 (4): 952–975. Google Scholar logo with link to Google Scholar
Carl, Michael, Barbara Dragstedt, and Arnt Lykke Jakobsen. 2011. “A Taxonomy of Human Translation Styles.” Accessed from: [URL], June 8, 2014.
Choudhury, Rahzeb, and Brian McConnell. 2013. TAUS Translation Technology Landscape Report. Accessed from: [URL], October 29, 2013.
Doherty, Stephen, and Sharon O’Brien. 2009. Can MT Output be Evaluated through Eye Tracking? MT Summit XII, Ottawa, Canada.
Doherty, Stephen, Sharon O’Brien, and Michael Carl. 2010. “Eye Tracking as an MT Evaluation Technique.” Machine Translation 24 (1):1–13. Google Scholar logo with link to Google Scholar
Doherty, Stephen, and Joss Moorkens. 2013. “Investigating the Experience of Translation Technology Labs: Pedagogical Implications.” Journal of Specialised Translation 19: 122–136. Accessed from: [URL], July 21, 2013.Google Scholar logo with link to Google Scholar
Fiederer, Rebecca, and Sharon O’Brien. 2009. “Quality and Machine Translation: A Realistic Objective?” Journal Of Specialised Translation 11: 52–74. Accessed from: [URL], February 3, 2013.Google Scholar logo with link to Google Scholar
Folaron, Deborah A. 2010. “Translation Tools.” In Handbook of Translation Studies: Volume 1 2010 X, ed. by Yves Gambier and Luc van Doorslaer, 429–436. Amsterdam: John Benjamins. Google Scholar logo with link to Google Scholar
He, Yifan, Yanjun Ma, Johann Roturier, Andy Way, and Josef van Genabith. 2010. “Improving the Post-editing Experience using Translation Recommendation: A user Study.” Proceedings of the 9th Annual AMTA Conference , 247–256, Denver. Accessed from: [URL], June 8, 2014.
Hofmann, Sascha. 2012. Prozessgestütztes Übersetzen: vom funktionsorientierten Übersetzungsprozess zum Geschäftsprozessmodell für die Dienstleistung Übersetzen. Lichtenberg: Harland media.Google Scholar logo with link to Google Scholar
Hvelplund, Kristian Tangsgaard. 2011. Allocation of Cognitive Resources in Translation an Eye-tracking and Key-logging Study. PhD thesis, Department of International Language Studies and Computational Linguistics, Copenhagen Business School.
Jakobsen, Arnt Lykke. 1999. “Translog Documentation.” Copenhagen Studies in Language 24: 149–184.Google Scholar logo with link to Google Scholar
. 2011. “Tracking Translators’ Keystrokes and Eye Movements with Translog.” In Methods and Strategies of Process Research Kapitel 4 (Benjamins Translation Library, Vol. 94), ed. by C. Alvstad, A. Hild, and E. Tiselius, 37–55. Amsterdam: John Benjamins Publishing Company. Google Scholar logo with link to Google Scholar
Kirchhoff, Katrin, Anne M. Turner, Amittai Axelrod, and Francisco Saavedra. 2011. “Application of Statistical Machine Translation to Public Health Information: A Feasibility Study.” Journal of the American Medical Information Association 18 (4): 473–478. Accessed from: [URL], March 13, 2013. Google Scholar logo with link to Google Scholar
Koehn, Philipp, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan Herbst. 2007. “Moses: Open Source Toolkit for Statistical Machine Translation.” ACL Companion Volume. Proceedings of the Demo and Poster Sessions , 177–180. Prague, Czech Republic, June 2007. Association for Computational Linguistics.
Koehn, Philipp. 2009. “A Web-Based Interactive Computer Aided Translation Tool.” Proceedings of the ACL-IJCNLP 2009 Software Demonstrations , 17–20. Suntec, Singapore.
. 2010a. Statistical Machine Translation. Cambridge: Cambridge University Press.Google Scholar logo with link to Google Scholar
. 2010b. “Enabling Monolingual Translators: Post-Editing vs. Options.” Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (HLT/NAACL) , 537–545. Los Angeles, California: Association for Computational Linguistics,. Accessed from: [URL], June 8, 2014.
Koponen, Maarit. 2012. “Comparing Human Perceptions of Post-editing Effort with Post-editing Operations.” Proceedings of the 7th Workshop on Statistical Machine Translation 2012 , 181–190. Montreal, Canada, Association for Computational Linguistics. Accessed from: [URL], March 5, 2013.
Koponen, Maarit, Wilker Aziz, Luciana Ramos, and Lucia Specia. 2012. “Post-editing Time as a Measure of Cognitive Effort.” Proceedings of the AMTA 2012. Workshop on Post-editing Technology and Practice (WPTP 2012) .
Krings, Hans. 2001. Repairing Texts: Empirical Investigations of Machine Translation Post-editing Processes. Translated (German into English) by G. Koby, G. Shreve, K. Mischerikow, and S. Litzer; ed. by G. Koby. Kent, OH: Kent State University Press Translation Studies Series.Google Scholar logo with link to Google Scholar
Langlais, Philippe, George Foster, and Guy Lapalme. 2000. “Unit Completion for a Computer-aided Translation Typing System.” Machine Translation 15 (4): 267–294. Google Scholar logo with link to Google Scholar
Laurian, Anne-Marie. 1984. “Machine Translation: What type of Post-editing on what type of Documents for what type of Users.” COLING, Association for Computational Linguistics , 236–238. Morristown, N.J. Accessed from: [URL], January 28, 2013.
Mertin, Elvira. 2006. Prozessorientiertes Qualitätsmanagement im Dienstleistungsbereich Übersetzen (Leipziger Studien zur angewandten Linguistik und Translatologie, 2). Frankfurt am Main: Lang.Google Scholar logo with link to Google Scholar
O’Brien, Sharon. 2002. “Teaching Post-editing: A Proposal for Course Content.” Sixth EAMT Workshop “Teaching Machine Translation” , 99–106. UMIST, Manchester, England, November 14–15, 2002. Accessed from: [URL], February 3, 2013.
. 2010a. “Introduction to Post‐Editing: Who, What, How and Where to Next? Tutorial.” Accessed from: [URL], February 1, 2013.
. 2010b. “Controlled Language and Readability.” In Translation and Cognition (American Translators Association Scholarly Monograph Series XV), ed. by Shreve, Gregory, and Erik Angelone, 143–168. Amsterdam: John Benjamins. Accessed from: [URL], January 31, 2013. Google Scholar logo with link to Google Scholar
. 2012. “Translation as Human-Computer Interaction.” Translation Spaces 1 (1): 101–122. Accessed from: [URL], January 31, 2013. Google Scholar logo with link to Google Scholar
O’Brien, Sharon, Johann Roturier, and Giselle de Almeida. 2009. “Post-Editing MT Output Views from the Researcher, Trainer, Publisher and Practitioner.” Accessed from: [URL], July 12, 2013.
Pérez, Celia Rico. 2012. “A Flexible Decision Tool for Implementing Post-editing Guidelines.” Localisation Focus 11 (1): 54–65. Accessed from: [URL], June 8, 2014.Google Scholar logo with link to Google Scholar
Plitt, Mirko, and François Masselot. 2010. “A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context.” The Prague Bulletin of Mathematical Linguistics NUMBER 9 (3): 7–16.Google Scholar logo with link to Google Scholar
Poulis, Alexandros, and David Kolovratnik. 2012. “To Post-edit or not to Post-edit? Estimating the Benefits of MT Post-editing for a European Organization.” AMTA-2012: Workshop on Post-editing Technology and Practice. Proceedings , San Diego, October 28, 2012. Accessed from: [URL], June 8, 2014.
Przybocki, Mark, Greogory Sanders, and Audrey Le. 2006. Edit Distance: A Metric for Machine Translation Evaluation. National Institute of Standards and Technology (NIST). Accessed from: [URL], July 22, 2013.Google Scholar logo with link to Google Scholar
Schaeffer, Moritz, and Michael Carl. 2014. “Measuring the Cognitive Effort of Literal Translation Processes.” In Workshop on Humans and Computer-assisted Translation, ed. by Ulrich Germann, 29–37. Association for Computational Linguistics, 2014.Google Scholar logo with link to Google Scholar
Specia, Lucia. 2011a. Quality Estimation of Machine Translation. Abstract to Video talk on the Homepage of DCU, School of Computing, Dublin City University. Posted by gconway 07/07/2011. Accessed from: [URL], June 8, 2014.Google Scholar logo with link to Google Scholar
. 2011b. “Exploiting Objective Annotations for Measuring Translation Post-editing Effort.” 15th Annual Conference of the European Association for Machine Translation , 73–80, Leuven, Belgium.
. 2013. “Statistical Machine Translation.” In Emerging Applications of Natural Language Processing: Concepts and New Research, ed. by S. Bandyopadhyay, S.K. Naskar, and A. Ekbal, 74–109. Hershey, PA: IGI Global. Google Scholar logo with link to Google Scholar
Tatsumi, Midori, Takako Aikawa, Kentaro Yamamoto, and Hitoshi Isahara. 2012. “How Good Is Crowd Post-Editing? Its Potential and Limitations.” Proceedings of the AMTA 2012 Workshop on Post-editing Technology and Practice (WPTP 2012) . Accessed from: [URL], June 8, 2014.
Temnikova, Irina. 2010. “A Cognitive Evaluation Approach for a Controlled Language Post-Editing Experiment.” 7th International Conference on Language Resources and Evaluation , Valletta, Malta.
TAUS Report. 2010a. Postediting in Practice. Accessed from: [URL], October 29, 2013.
TAUS Translation in the 21st Century. 2010b. “What machines can’t translate... yet?” Accessed from: [URL], June 8, 2014.
TAUS/CNGL: Machine Translation Post-Editing Guidelines Published. Accessed from: [URL], October 29, 2013.
Van der Meer, Jaap. 2013. Choose your Own Translation Future. Accessed from: [URL], January 28, 2013.
Vashee, Kirti. 2011. An Exploration on Post-Editing MT – Part I. Accessed Blog from: [URL], June 8, 2014.
Wagner, Emma. 1985. “Post-Editing Systran – A Challenge for Commission Translator.” Terminologie et Traduction 3.Google Scholar logo with link to Google Scholar
. 1987. “Post-editing—Practical Considerations.” In The Business of Translation and Interpreting, ed. by Catriona Picken, 71–78. London: Aslib.Google Scholar logo with link to Google Scholar
Winther-Balling, Laura, and Michael Carl. 2014. “Production time across languages and tasks: A large-scale analysis using the critt translation process database.” In The Development of Translation Competence: Theories and Methodologies from Psycholinguistics and Cognitive Science, ed. by J.W. Schwieter and A. Ferreira, 239–268. Newcastle upon Tyne, UK: Cambridge Scholars Publishing.Google Scholar logo with link to Google Scholar
Cited by (20)

Cited by 20 other publications

Sdobnikov, V. V.
2025. AI in Translation: How to Use it Effectively. Nauchnyi dialog 14:3 ► pp. 62 ff. DOI logo
Lesznyák, Márta, Mária Bakti & Eszter Sermann
2024. Reading takes it all? – the role of language competence and subject knowledge in legal translation. The Interpreter and Translator Trainer 18:2 ► pp. 192 ff. DOI logo
Sun, Juan, Zhi Lu, Isabel Lacruz, Lijun Ma, Lin Fan, Xiuhua Huang & Bo Zhou
2023. An eye-tracking study of productivity and effort in Chinese-to-English translation and post-editing. In Translation in Transition [American Translators Association Scholarly Monograph Series, XX], ► pp. 57 ff. DOI logo
Cennamo, Ilaria & Loïc de Faria Pires
2022. Intelligence artificielle et traduction. FORUM. Revue internationale d’interprétation et de traduction / International Journal of Interpretation and Translation 20:2 ► pp. 333 ff. DOI logo
He, Shaobin, Yunhan Hao, Shijie Liu, Huidan Liu & Huadong Li
2022. Research on translation technology teaching in Chinese publications and in international English-language publications (1999-2020): a bibliometric analysis. The Interpreter and Translator Trainer 16:3 ► pp. 275 ff. DOI logo
Malmkjær, Kirsten
2022. Translation Studies fifty years on. Translation and Translanguaging in Multilingual Contexts 8:3 ► pp. 211 ff. DOI logo
Jiménez-Crespo, Miguel A. & Joseph V. Casillas
2021. Literal is not always easier. Translation, Cognition & Behavior 4:1 ► pp. 98 ff. DOI logo
Massey, Gary & Regine Wieder
2019. Quality Assurance in Translation and Corporate Communications. In Quality Assurance and Assessment Practices in Translation and Interpreting [Advances in Linguistics and Communication Studies, ], ► pp. 57 ff. DOI logo
Castilho, Sheila, Stephen Doherty, Federico Gaspari & Joss Moorkens
2018. Approaches to Human and Machine Translation Quality Assessment. In Translation Quality Assessment [Machine Translation: Technologies and Applications, 1], ► pp. 9 ff. DOI logo
Huang, Jin
2018. Working styles of student translators in self-revision, other-revision and post-editing. In Eye tracking and multidisciplinary studies on translation [Benjamins Translation Library, 143], ► pp. 145 ff. DOI logo
Moorkens, Joss
2018. Eye tracking as a measure of cognitive effort for post-editing of machine translation. In Eye tracking and multidisciplinary studies on translation [Benjamins Translation Library, 143], ► pp. 55 ff. DOI logo
Moorkens, Joss, Antonio Toral, Sheila Castilho & Andy Way
2018. Translators’ perceptions of literary post-editing using statistical and neural machine translation. Translation Spaces 7:2 ► pp. 240 ff. DOI logo
O’Brien, Sharon, Michel Simard & Marie-Josée Goulet
2018. Machine Translation and Self-post-editing for Academic Writing Support: Quality Explorations. In Translation Quality Assessment [Machine Translation: Technologies and Applications, 1], ► pp. 237 ff. DOI logo
Forstner, Martin
2017. Des Translators neue Kleider.Die Translationwirtschaft in Zeiten von Digitalisierung, Datafizierung und Big Data Management. Lebende Sprachen 62:2 ► pp. 333 ff. DOI logo
Lourenço da Silva, Igor A., Fabio Alves, Márcia Schmaltz, Adriana Pagano, Derek Wong, Lidia Chao, Ana Luísa V. Leal, Paulo Quaresma, Caio Garcia & Gabriel Eduardo da Silva
2017. Translation, post-editing and directionality. In Translation in Transition [Benjamins Translation Library, 133], ► pp. 107 ff. DOI logo
Mellinger, Christopher D.
2017. Translators and machine translation: knowledge and skills gaps in translator pedagogy. The Interpreter and Translator Trainer 11:4 ► pp. 280 ff. DOI logo
Carl, Michael, Srinivas Bangalore & Moritz J. Schaeffer
2016. Computational linguistics and translation studies. In Border Crossings [Benjamins Translation Library, 126], ► pp. 225 ff. DOI logo
Martikainen, Hanna & Natalie Kübler
2016. Ergonomie cognitive de la post-édition de traduction automatique : enjeux pour la qualité des traductions. ILCEA :27 DOI logo
Nitzke, Jean & Katharina Oster
2016. Comparing Translation and Post-editing: An Annotation Schema for Activity Units. In New Directions in Empirical Translation Process Research [New Frontiers in Translation Studies, ], ► pp. 293 ff. DOI logo
[no author supplied]
2024. , DOI logo

This list is based on CrossRef data as of 15 november 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Mobile Menu Logo with link to supplementary files background Layer 1 prag Twitter_Logo_Blue