Augmented translation is a new approach to combining the strengths of humans and machines to address growing needs for multilingual content. In contrast to traditional post-editing, which leaves translators at the end of a process and asks them to clean up garbage machine translation (MT) ouput, augmented translation places linguists at the center of a constellation of technologies that support them and extend their capabilities: enhanced translation memory, adaptive neural machine translation, automated content enrichment, next-generation terminology management, lights-out project management, and microservices-based translation management systems. The results increase the productivity and value of human linguists by providing relevant information and letting them focus on those aspects of translation that require their attention.

This an update of our previously published “How AI Will Augment Human Translation.” CSA Research reexamined and updated this research to include the results of technology developments since its publication and to reflect the latest conceptual frameworks from our discussions and briefings with creators of translation tools.

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