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.
The introduction of machine translation in a company is a serious step that raises many questions regarding its technical implementation, its incorporation into the existing translation workflow and its effect upon data security and cost efficiency. Because of the newly sparked interest in the general applicability of machine translation caused by NMT (Neural Machine Translation), we are dedicating a longer article to this subject aiming to answer some fundamental questions and to prepare the ground for an initial assessment.