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.
One of the first things a foreigner faces when coming to a new country is language. And one of the first things that a non-native speaker observes is that the language native speakers use in everyday life is quite different from the one taught at school or at university. As a linguist I find it exciting to be exposed to a great variety of German language phenomena every day. Idioms is one of them. But why are people using idioms in their everyday speech?
Those were my thoughts when I flew to Singapore for the 2-day TAUS Asia Congress. I wanted to have confirmed (or refuted) what was reported in the domestic media. How this turned out? Find out in this blog.
The TAUS (Translation Automation User Society) Global Content Summit was once more held in Dublin chez Microsoft. Well protected from the first storm runners, I was able to spend a day exchanging inspiring thoughts with language process and technology experts from LSPs, technology providers and industry giants.
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.
It was in one word - supercalifragilisticexpialidocious! 64 SDL power users and colleagues from 10 countries met at the ETUG (European Trados User Group) in Düsseldorf and talked about (almost) nothing but SDL tools, apps, workflows, road maps, use cases and innovations for two days.
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.