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Towards predicting post-editing productivity

O'Brien, Sharon (2011) Towards predicting post-editing productivity. Machine Translation, 25 (1). pp. 197-215. ISSN 0922-6567

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Machine translation (MT) quality is generally measured via automatic metrics, producing scores that have no meaning for translators who are required to post-edit MT output or for project managers who have to plan and budget for transla- tion projects. This paper investigates correlations between two such automatic metrics (general text matcher and translation edit rate) and post-editing productivity. For the purposes of this paper, productivity is measured via processing speed and cognitive measures of effort using eye tracking as a tool. Processing speed, average fixation time and count are found to correlate well with the scores for groups of segments. Segments with high GTM and TER scores require substantially less time and cognitive effort than medium or low-scoring segments. Future research involving score thresholds and confidence estimation is suggested.

Item Type:Article (Published)
Uncontrolled Keywords:Post-editing; Productivity; Cognitive effort; Automatic metrics for MT; Eye tracking
Subjects:Computer Science > Machine translating
Humanities > Translating and interpreting
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Applied Language and Intercultural Studies
Official URL:
Copyright Information:©2011 Springer-Kluwer The original publication is available at
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Centre for Next Generation Localisation
ID Code:17154
Deposited On:04 Oct 2012 11:56 by Sharon O'Brien. Last Modified 04 Oct 2012 11:56

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