Using machine translation in computer-aided translation to suggest the target-side words to change

Abstract

This paper explores the use of machine translation (MT) to help users of computer-aided translation systems based on translation memory to identify the target words in the translation proposals that need to be changed or kept unedited. MT is used as a black box to obtain a set of features for each target word in the translation proposals and then used by a binary classifier to determine the target words to change or keep unedited. Experiments conducted in the translation of Spanish texts into English with different corpora shows an accuracy above 96% for fuzzy-match scores above 70%.