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Article published In:
The Journal of Internationalization and Localization
Vol. 5:2 (2018) ► pp.114–141

Translating the same text twice

An English-Spanish comparative product study of post-edited translations vs. human translations

| University of North Carolina at Charlotte

This article presents the results of a study in which students in a graduate translation technologies course post-edited a text they had previously translated earlier in the semester without using machine translation (MT). The results show that post-editing allowed students with performance levels below, at, and just above an established median to improve the quality of their translation products, while students with performances well above the median actually experienced a decrease in quality. Nevertheless, the post-edited products and post-editing performances of the latter remained superior to those of the former. The study shows how different translators experienced gains or not in quality by accepting different aspects of MT output and how the accepted output relates to their human renditions. It also tracks whether their post-edits were necessary and correct and how they relate to their human renditions. Tracking such behaviors attempts to provide a more holistic view of how post-editing might be qualitatively advantageous or disadvantageous.

Keywords: post-editing, translation pedagogy, machine translation, translation technologies
Article outline
  • 1.Introduction
  • 2.Related research
  • 3.The study
    • 3.1The task
    • 3.2The participants and texts
    • 3.3Comparison of translation renditions
    • 3.4The main hypothesis (HP1) and sub-hypotheses (HP1.1, HP1.2, and HP1.3)
  • 4.Analysis of results
    • 4.1Text difficulty and translator performance
    • 4.2Results of the translation errors analysis
    • 4.3What the participants did with the MT output
      • 4.3.1Second sub-hypothesis (HP1.2)
      • 4.3.2Third sub-hypothesis (HP1.3)
  • 5.Discussion
  • 6.Conclusions
  • Notes
  • References
Published online: 21 January 2019
DOI logo
https://doi.org/10.1075/jial.18003.kil
References

References

Belam, Judith
2003 “Buying up to Falling Down: A Deductive Approach to Teaching Post-Editing.” In MT Summit IX, Workshop on Teaching Translation Technologies and Tools. New Orleans, USA.Google Scholar
Bendana, Lola, and Alan Melby
2012 Almost Everything You Ever Wanted to Know about Translation. Toronto: Multi-Languages Corporation. [URL]
Castilho, Sheila, Joss Moorkens, Federico Gaspari, Iacer Calixto, John Tinsley, and Andy Way
2017 “Is Neural Machine Translation the New State of the Art?” The Prague Bulletin of Mathematical Linguistics 1081 (June 2017): 109–120. DOI logoGoogle Scholar
DePalma, Donald A., and Benjamin B. Sargent
2013 Translation Services and Software in the Cloud: How LSPs Will Move to Cloud-Based Solutions. Lowell, MA: Common Sense Advisory.Google Scholar
Depraetere, Ilse
2010 “What Counts as Useful Advice in a University Post-Editing Training Context? Report on a Case Study.” In EAMT 2010: Proceedings of the 14th Annual Conference of the European Association for Machine Translation. Saint-Raphaël, France.Google Scholar
Dillinger, Mike
2017 “Interview with Mike Dillinger, Machine Translation Pioneer, by Tony Beckwith.” The ATA Chronicle XLVI (2): 27–30.Google Scholar
Doherty, Stephen, and Dorothy Kenny
2014 “The Design and Evaluation of a Statistical Machine Translation Syllabus for Translation Students.” The Interpreter and Translator Trainer 8.21: 295–315. DOI logoGoogle Scholar
García, Ignacio
2010 “Is Machine Translation Ready Yet?” Target, 22 (1): 7–21. DOI logoGoogle Scholar
2011 “Translating by Post-Editing: Is it the Way Forward?” Machine Translation 251: 217–237. DOI logoGoogle Scholar
Gaspari, Federico, Hala Almaghout, and Stephen Doherty
2015 “A Survey of Machine Translation Competences: Insights for Translation Technology Educators and Practitioners.” Perspectives: Studies in Translatology 23 (3): 333–358. DOI logoGoogle Scholar
Gile, Daniel
1999 “Testing the Effort Models’ Tightrope Hypothesis in Simultaneous Interpreting – A Contribution.” Hermes 231: 153–172.Google Scholar
Guerberof Arenas, Ana
2010 “Exploring Machine Translation on the Web.” Revista Tradumática 81: 1–6. [URL].
Guzmán, Rafael
2007 “Manual MT Post-editing: If it’s not Broken, don’t Fix it!” Translation Journal 11 (4). [URL].
Hutchins, John
2003 “The Development and Use of Machine Translation Systems and Computer-Based Translation Tools.” International Journal of Translation 15 (1): 5–26.Google Scholar
Kelly, Nataly, Donald A. DePalma, and Robert G. Stewart
2012 The Language Services Market: 2012 – An Annual Review of the Translation, Localization, and Interpreting Services Industry. Lowell, MA: Common Sense Advisory.Google Scholar
Kenny, Dorothy, and Stephen Doherty
2014 “Statistical Machine Translation in the Translation Curriculum: Overcoming Obstacles and Empowering Translators.” The Interpreter and Translator Trainer 8 (2): 276–294. DOI logoGoogle Scholar
Killman, Jeffrey
2014 “Vocabulary Accuracy of Statistical Machine Translation in the Legal Context.” In Proceedings of the Third Workshop on Post-Editing Technology and Practice (WPTP-3), The 11th Conference of the Association for Machine Translation in the Americas, 22–26 October 2014, Vancouver, BC Canada, by Sharon O’Brien, Michel Simard, and Lucia Specia, 85–98. Vancouver: AMTA.Google Scholar
2016 “Introducing Machine Translation in Translator Training: Comparing ‘Information Mining’ with Post-Editing.” EntreCulturas 7–8: 179–193.Google Scholar
Kliffer, Michael
2005 “An experiment in MT post-editing by a class of intermediate/advanced French majors.” In EAMT 2005 Conference Proceedings, 160–165. Budapest, Hungary.Google Scholar
Lee, Jason, and Posen Liao
2011 “A Comparative Study of Human Translation and Machine Translation with Post-Editing.” Compilation and Translation Review 4(2): 105–149.Google Scholar
Mellinger, Christopher D.
2017 “Translators and Machine Translation: Knowledge and Skills Gaps in Translator Pedagogy.” The Interpreter and Translator Trainer 11 (4): 280–293. DOI logoGoogle Scholar
Mellinger, Christopher D., and Gregory M. Shreve
2016 “Match Evaluation and Over-Editing in a Translation Memory Environment.” In Reembedding Translation Process Research, by Ricardo Muñoz Martín, 131–148. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Mossop, Brian
1992 “Goals of a Revision Course.” In Teaching Translation and Interpreting: Training, Talent, and Experience, by Cay Dollerup and Anne Loddegaard. Philadelphia: John Benjamins. DOI logoGoogle Scholar
2007 “Empirical Studies of Revision: What We Know and Need to Know.” The Journal of Specialized Translation 81 (July 2007): 5–20Google Scholar
O’Brien, Sharon
2002 “Teaching Post-Editing: A Proposal for Course Content.” In 6th EAMT Workshop, Teaching Machine Translation, 99–106. Manchester, UK. Manchester, UK.Google Scholar
Phelan, Mary
2017 “Analytical Assessment of Legal Translation: A Case Study Using the American Translators Association Framework.” The Journal of Specialized Translation 271 (January 2017): 189–210Google Scholar
Pym, Anthony
2009 “Using Process Studies in Translator Training: Self-Discovery through Lousy Experiments.” In Methodology, Technology and Innovation in Translation Process Research, by Susanne Göpferich, Fabio Alves, and Inge Mees, 135–156. Copenhagen: Samfundslitteratur.Google Scholar
2011 “What Technology Does to Translating.” Translation & Interpreting 3 (1): 1–9.Google Scholar
2013 “Translation Skill-Sets in a Machine-translation Age.” Meta 58(3): 487–503. DOI logoGoogle Scholar
Şahin, Mehmet, and Nilgün Dungan
2014 “Translation Testing and Evaluation: a Study on Methods and Needs.” Translation & Interpreting, 6(2), 67–90.Google Scholar
Sánchez Gijón, Pilar, and Olga Torres-Hostench
2014 “MT Post-Editing into the Mother Tongue or into a Foreign Language? Spanish-to-English MT Translation Output Post-Edited by Translation Trainees.” In Proceedings of the Third Workshop on Post-Editing Technology and Practice (WPTP-3), The 11th Conference of the Association for Machine Translation in the Americas, 22–26 October 2014, Vancouver, BC Canada, by Sharon O’Brien, Michel Simard, and Lucia Specia, 5–19. Vancouver: AMTA.Google Scholar
Singh, Nitish
2012 Localization Strategies for Global E-Business. New York: Cambridge University Press.Google Scholar
TAUS
2017 Machine Translation Market Report. [URL]
Yamada, Masaru
2015 “Can College Students be Post-Editors? An Investigation into Employing Language Learners in Machine Translation plus Post-Editing Settings.” Machine Translation 29 (1): 49–67. DOI logoGoogle Scholar
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