Browsing Category : machine translation

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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Linguistics To Go: It’s all about food

Linguistics To Go: It’s all about food
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?
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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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Machine translation in corporate environments – is it worth it?

Machine translation in corporate environments – is it worth it?
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.
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