Abstract

For several language pairs, an emerging consensus finds that post-editing of machine translations is faster and less cognitively effortful than from-scratch human translation, resulting in increased translator productivity and decreased translator fatigue. These benefits have yet to be robustly established in some language pairs that are linguistically and culturally remote with very different writing systems. We carry out a systematic Chinese-to-English study using keystroke logger timing measures and eye-tracking measures of cognitive effort, taking into account translator education levels, different source text domains, and quality of the translation product. We observe significant post-editing productivity gains for more highly educated participants and for more straightforward and less technical texts. Measures of cognitive effort show significantly reduced cognitive effort in post-editing.

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