Saarland University researchers are developing an automated system for translating between the languages of the European Union (EU) so comprehensible texts are achieved for as many language combinations as possible.
Due to the complexity of some EU languages, the researchers taught the computers to recognize patterns in huge text repositories and to learn from them, instead of feeding the computers with grammar rules and linguistic details. "This machine learning strategy has nothing to do with natural intelligence, but it does have similarities with the processes that occur in the human brain when we control the muscles in our bodies," says Saarland University professor Josef van Genabith.
The Saarland researchers are working with QT21, a consortium of 14 leading research institutions for machine translation in Europe and Hong Kong, which includes universities, research institutions, and private companies. "Our common goal is to exploit machine learning to significantly improve automatic translation, particularly of more complex languages such as Latvian or Czech," van Genabith says.
Meanwhile, van Genabith and the German Research Center for Artificial Intelligence also are leading the European Language Resources Coordination, which aims to collect suitable language datasets that will enable the European Commission's automated translation platform to be adapted and optimized for daily requirements of public administrators in all EU member states.
From Saarland University
View Full Article
Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA