Machine Translation (MT) has experienced remarkable improvements and consequently grown in popularity of late. It now functions not only as an end in itself but also as a valuable asset to be exploited by translators in the promising practice of post-editing the outcome of MT systems, which can yield faster and sometimes more accurate results. Most systems, however, were not originally designed having translators envisaged as potential users, which leaves a high demand for tools capable of catering for this new translation modality. With the purpose of showcasing what researchers and the industry have to offer in that respect, this study provides a review of a number of currently available translation tools from the perspective of translation post-editing. We have selected and described toolkits according to a set of criteria, highlighting main differences and similarities between them and also making mention of desirable features that have not been satisfactorily presented by any of the toolkits
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