Browsing Tag : Post-Editing

Neural Machine Translation powered by the Crowd

Neural Machine Translation powered by the Crowd

The Neural Machine Translation (NMT) train is rapidly picking up speed and NMT has long since arrived in Germany. This is due to the widespread use of the NMT flagship DeepL as well as the growing interest of small and large companies in integrating specialized customer-specific MT into the translation workflow. In my blog, I deal with everyday questions about the service provider landscape, training possibilities for domain-specific engines and the implementation of post-editing processes.

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Measuring machine translation quality with SDL WorldServer and TAUS DQF

Measuring machine translation quality with SDL WorldServer and TAUS DQF
Whenever machine translation (MT) components are introduced to a translation workflow, the system or engine must first prove itself in terms of quality and usability.  To find out whether the engine meets all requirements, an initial series of data surveys is necessary. Only on such grounds it is possible to get an impression of quality or productivity growth. In today's blog we explain how to measure the quality of automatic translations with the Dynamic Quality Framework (DQF) by TAUS.
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