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In the context of linguistic services, post-editing is the job of reviewing and correcting raw machine translation output to ensure that final results meet quality expectations. Before beginning the post editing step, a document is firstly processed by machine translation engines -software developed for automated translation- to have it translated automatically. Following the first step, the raw output is reviewed and edited by human translators -also called post editors- for possible issues such as incorrect and missing translations, inconsistencies, terminology errors.
Based on the extent of the changes implemented, there are two types of it: light post editing and full post editing. While the first one involves making as few modifications as possible to make the translation understandable, full post editing requires to implement all the necessary changes to increase the final translation quality to a level comparable to human translation.
Post editing is not a new practice. However, it has become a more common implementation in parallel with the latest developments in machine translation technology. With the rise of machine translation usage, requests for post editing jobs are also increasing to reap the benefits of improved productivity and reduced costs.
Such a hybrid workflow, which combines the speed of machine translation with the experience of human linguists, helps to shrink costs and soar productivity particularly for the content types that have a consistent style and terminology, repetitive and uncomplicated sentence structures, nonmetaphorical and straightforward message.
When implemented on a raw machine translation output, post editing helps to improve the final quality of translation as it is a step performed by human translators. Although machine translation systems are now producing better results when compared to the past, translations generated by automated translation engines might still need improvements depending on where the translation will be used and the quality expectations. This is where post editing comes in to help eliminate any possible issues in machine translated texts with the help of professional translators.
What makes post editing more efficient?
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