Abstract is missing.
- How Good Is Crowd Post-Editing? Its Potential and LimitationsMidori Tatsumi, Takako Aikawa, Kentaro Yamamoto, Hitoshi Isahara. [doi]
- SmartMATE: An Online End-To-End MT Post-Editing FrameworkSergio Penkale, Andy Way. [doi]
- Post-editing time as a measure of cognitive effortMaarit Koponen, Wilker Aziz, Luciana Ramos, Lucia Specia. [doi]
- Error Detection for Post-editing Rule-based Machine TranslationJustina Valotkaite, Munshi Asadullah. [doi]
- Average Pause Ratio as an Indicator of Cognitive Effort in Post-Editing: A Case StudyIsabel Lacruz, Gregory M. Shreve, Erik Angelone. [doi]
- Machine Translation Infrastructure and Post-editing Performance at AutodeskVentsislav Zhechev. [doi]
- The CRITT TPR-DB 1.0: A Database for Empirical Human Translation Process ResearchMichael Carl. [doi]
- To post-edit or not to post-edit? Estimating the benefits of MT post-editing for a European organizationAlexandros Poulis, David Kolovratnik. [doi]
- Reliably Assessing the Quality of Post-edited Translation Based on Formalized Structured Translation SpecificationsAlan K. Melby, Jason Housley, Paul J. Fields, Emily Tuioti. [doi]
- Learning to Automatically Post-Edit Dropped Words in MTJacob Mundt, Kristen Parton, Kathleen R. McKeown. [doi]