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A virtuous circle: laundering translation memory data using statistical machine translation

, , , and . Perspectives: Studies in Translatology, 22 (3): 291--303 (October 2014)
DOI: 10.1080/0907676X.2013.811275

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A virtuous circle: laundering translation memory data using statistical machine translation, , , and . Perspectives: Studies in Translatology, 22 (3): 291--303 (October 2014)Evaluating the Impact of Light Post-Editing on Usability., and . LREC, European Language Resources Association (ELRA), (2016)Correlations of perceived post-editing effort with measurements of actual effort., , , , and . Mach. Transl., 29 (3-4): 267-284 (2015)Towards predicting post-editing productivity.. Mach. Transl., 25 (3): 197-215 (2011)Introduction to Post-Editing: Who, What, How and Where to Next?. AMTA (Tutorials), Association for Machine Translation in the Americas, (2010)A Novel Statistical Pre-Processing Model for Rule-Based Machine Translation System., , , and . EAMT, European Association for Machine Translation, (2010)Post-Editing Evaluations: Trade-offs between Novice and Professional Participants., and . EAMT, European Association for Machine Translation, (2015)What is the impact of raw MT on Japanese users of Word: preliminary results of a usability study using eye-tracking., , and . MTSummit (1), page 67-77. European Association for Machine Translation, (2019)How portable are controlled language rules? A comparison of two empirical MT studies., and . MTSummit, (2007)The INTERACT Project and Crisis MT., , , , , , , and . MTSummit (2), page 38-48. (2017)