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How Good Is Crowd Post-Editing?

Midori Tatsumi, Takako Aikawa, Kentaro Yamamoto, and Hitoshi Isahara


This paper is a partial report of a research effort on evaluating the effect of crowd-sourced post-editing. We first discuss the emerging trend of crowd-sourced post-editing of machine translation output, along with its benefits and drawbacks. Second, we describe the pilot study we have conducted on a platform that facilitates crowd-sourced post-editing. Finally, we provide our plans for further studies to have more insight on how effective crowd-sourced post-editing is.


Publication typeProceedings
PublisherProceedings of Association for Machine Translation in the Americas (AMTA)
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