Correlations between productivity and quality when post-editing in a professional context

This article presents results on the correlation between machine-translated and fuzzy matches segments in terms of productivity and final quality in the context of a localization project. In order to explore these two aspects, we set up an experiment with a group of twenty four professional translators using an online post-editing tool and a customized Moses machine translation engine with a BLEU score of 0.60. The translators were asked to translate from English to Spanish, working on no-match, machine-translated and translation memory segments from the 85-94 percent value, using a post-editing tool, without actually knowing if the segment came from machine translation or from translation memory. The texts were corrected by three professional reviewers to assess the final quality of the assignment. The findings suggest that translators have higher productivity and quality when using machine-translated output than when translating without it, and that this productivity and quality is not significantly different from the values obtained when processing fuzzy matches from translation memories in the range 85-94 percent