Post-editing human translations and revising machine translations : impact on efficiency and quality
- Author
- Joke Daems (UGent) and Lieve Macken (UGent)
- Organization
- Project
- Abstract
- Post-editing of machine-translation output is generally considered to be a distinct process from the revision of a human-translated text. The main reasons for this assumption are the quality of machine-translation output and the fact that it might be easier to criticize the work of a machine than the work of a fellow human translator. With the global shift of statistical machine-translation systems to neural machine-translation systems, however, the quality of machine-translation output has improved. What was true about differences between revision and post-editing in 2010 might therefore no longer be true today. In addition, translators hired to revise a text are not always aware of the origin of the text. This chapter compares revision and post-editing products made by professional translation agencies when the actual origin of a text corresponded to the instructions they were given (revision of a human translation, post-editing of machine translation) and when the origin did not match the instructions (post-editing of a human translation and revision of machine translation). We look at the number of edits made, the quality of the revision and the optimality of the intervention.
- Keywords
- lt3, machine translation, post-editing, revision
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8689123
- MLA
- Daems, Joke, and Lieve Macken. “Post-Editing Human Translations and Revising Machine Translations : Impact on Efficiency and Quality.” Translation Revision and/or Post-Editing : Industry Practices and Cognitive Processes, edited by Maarit Koponen et al., Routledge, 2020, pp. 50–70, doi:10.4324/9781003096962-5.
- APA
- Daems, J., & Macken, L. (2020). Post-editing human translations and revising machine translations : impact on efficiency and quality. In M. Koponen, B. Mossop, I. Robert, & G. Scocchera (Eds.), Translation revision and/or post-editing : industry practices and cognitive processes (pp. 50–70). https://doi.org/10.4324/9781003096962-5
- Chicago author-date
- Daems, Joke, and Lieve Macken. 2020. “Post-Editing Human Translations and Revising Machine Translations : Impact on Efficiency and Quality.” In Translation Revision and/or Post-Editing : Industry Practices and Cognitive Processes, edited by Maarit Koponen, Brian Mossop, Isabelle Robert, and Giovanna Scocchera, 50–70. London; New York: Routledge. https://doi.org/10.4324/9781003096962-5.
- Chicago author-date (all authors)
- Daems, Joke, and Lieve Macken. 2020. “Post-Editing Human Translations and Revising Machine Translations : Impact on Efficiency and Quality.” In Translation Revision and/or Post-Editing : Industry Practices and Cognitive Processes, ed by. Maarit Koponen, Brian Mossop, Isabelle Robert, and Giovanna Scocchera, 50–70. London; New York: Routledge. doi:10.4324/9781003096962-5.
- Vancouver
- 1.Daems J, Macken L. Post-editing human translations and revising machine translations : impact on efficiency and quality. In: Koponen M, Mossop B, Robert I, Scocchera G, editors. Translation revision and/or post-editing : industry practices and cognitive processes. London; New York: Routledge; 2020. p. 50–70.
- IEEE
- [1]J. Daems and L. Macken, “Post-editing human translations and revising machine translations : impact on efficiency and quality,” in Translation revision and/or post-editing : industry practices and cognitive processes, M. Koponen, B. Mossop, I. Robert, and G. Scocchera, Eds. London; New York: Routledge, 2020, pp. 50–70.
@incollection{8689123,
abstract = {{Post-editing of machine-translation output is generally considered to be a distinct process from the revision of a human-translated text. The main reasons for this assumption are the quality of machine-translation output and the fact that it might be easier to criticize the work of a machine than the work of a fellow human translator. With the global shift of statistical machine-translation systems to neural machine-translation systems, however, the quality of machine-translation output has improved. What was true about differences between revision and post-editing in 2010 might therefore no longer be true today. In addition, translators hired to revise a text are not always aware of the origin of the text. This chapter compares revision and post-editing products made by professional translation agencies when the actual origin of a text corresponded to the instructions they were given (revision of a human translation, post-editing of machine translation) and when the origin did not match the instructions (post-editing of a human translation and revision of machine translation). We look at the number of edits made, the quality of the revision and the optimality of the intervention.}},
author = {{Daems, Joke and Macken, Lieve}},
booktitle = {{Translation revision and/or post-editing : industry practices and cognitive processes}},
editor = {{Koponen, Maarit and Mossop, Brian and Robert, Isabelle and Scocchera, Giovanna}},
isbn = {{9781138549715}},
keywords = {{lt3,machine translation,post-editing,revision}},
language = {{eng}},
pages = {{50--70}},
publisher = {{Routledge}},
title = {{Post-editing human translations and revising machine translations : impact on efficiency and quality}},
url = {{http://doi.org/10.4324/9781003096962-5}},
year = {{2020}},
}
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