Supporting a Data-driven MT Program in memoQ

With the recent boom in NMT, more and more companies consider it a way to reduce their translation costs. But is it really a holy grail? Is it finally time to deploy MT into production? Is it worth maintaining an MT engine at all? What are the actual savings? How can discounts be justified? I’m afraid there are no one-size-fits-all answers to these questions, as they may differ for each and every environment. Instead, the goal of my presentation is to demonstrate how memoQ can support a data-driven MT-based program by enabling human evaluations, providing a wealth of data, producing relevant statistics, enhancing long-term quality tracking and influencing MT deployment decisions.


Miklós Urbán
Senior Solutions Architect, RWS Moravia

Miklós is an industry expert and renowned for his knowledge of memoQ based localization systems. He has experience in many roles including operations and production manager of translation agencies as well as manager of professional services at memoQ. Currently, he works for RWS Moravia as senior solutions architect and provides support for the localization solutions of some major localization buyers. His primary focus nowadays is utilizing NMT and AI in translation workflows.