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A new deal for translation quality

Aljoscha Burchardt; Arle Lommel; Vivien Macketanz
In: Universal Access in the Information Society, Vol. 20?, Pages 1-15, Springer, 2020.


Given the rich body of technical developments and a relatively long history of industrial use of Machine Translation (MT), it is astonishing of how little interest the topic of MT quality has received so far. In this paper, we present three ways of performing MT quality evaluation from our own research: (1) using TQ-AutoTest, a framework for semi-automatic testing and comparison of different translation engines; (2) applying the multidimensional quality metrics for analytical markup of translation errors; and (3) performing task-based user testing. We will set these three in perspective as they serve different needs and different people’s interest in translation quality assessment. This paper deals with the translation of text in the first place. Still, we hope that the methods, insights, and observations we report transfer to broader applications of translation in the field of Media Accessibility.


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