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Post-editing effort of a novel with statistical and neural machine translation

Toral, Antonio, Wieling, Martijn and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2018) Post-editing effort of a novel with statistical and neural machine translation. Frontiers in Digital Humanities, 5 (9). pp. 1-11. ISSN 2297-2668

We conduct the first experiment in the literature in which a novel is translated automatically and then post-edited by professional literary translators. Our case study is Warbreaker, a popular fantasy novel originally written in English, which we translate into Catalan. We translated one chapter of the novel (over 3,700 words, 330 sentences) with two data-driven approaches to Machine Translation (MT): phrase-based statistical MT (PBMT) and neural MT (NMT). Both systems are tailored to novels; they are trained on over 100 million words of fiction. In the post-editing experiment, six professional translators with previous experience in literary translation translate subsets of this chapter under three alternating conditions: from scratch (the norm in the novel translation industry), post-editing PBMT, and post-editing NMT. We record all the keystrokes, the time taken to translate each sentence, as well as the number of pauses and their duration. Based on these measurements, and using mixed-effects models, we study post-editing effort across its three commonly studied dimensions: temporal, technical and cognitive. We observe that both MT approaches result in increases in translation productivity: PBMT by 18%, and NMT by 36%. Post-editing also leads to reductions in the number of keystrokes: by 9% with PBMT, and by 23% with NMT. Finally, regarding cognitive effort, post-editing results in fewer (29 and 42% less with PBMT and NMT, respectively) but longer pauses (14 and 25%).
Item Type:Article (Published)
Additional Information:The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fdigh. 2018.00009/full#supplementary-material
Uncontrolled Keywords:literary translation; post-editing; neural machine translation; statistical machine translation; foreign literature; foreign fiction
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:UNSPECIFIED
Publisher:Frontiers Media
Official URL:http://dx.doi.org/10.3389/fdigh.2018.00009
Copyright Information:© 2018 The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:23364
Deposited On:27 May 2019 15:29 by Thomas Murtagh . Last Modified 30 May 2019 13:23

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