Introducing TAUS' "hi-fi" translation data service
Six years ago in 2013, a Dutch government funded research project was launched in Amsterdam under the leadership of Professor Khalil Sima’an, a computational linguist at the Institute for Logic, Language and Computation of the University of Amsterdam. Called DatAptor, it brought together a team from Intel, the Directorate General of Translation of the European Commission, and TAUS, the translation automation think tank.
The partners set themselves a critical machine translation (MT) goal: How to make it more efficient to immediately select the very best translation data for an MT engine from the vast amount of available content. Three years later, their response emerged as a brand new online service – the TAUS Matching Data solution.
Language data is in demand right across the technology map as machine learning solutions are used for applications such as chatbots, automated report ...
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