How can we cope with all the content on the Web and make it available to interested people, regardless of the language(s) they speak and understand? The obvious answer is to teach computers how to understand and process written and spoken human language.
The online market (the Digital Single Market) remains fragmented by significant language barriers, despite the European Single Market should allow for free circulation of goods and services.
These barriers hinder online commerce, social communication and exchange of cultural content, as well as the wider deployment of pan-European public services.
Machine translation (MT) solutions available on the market usually don't reach the required levels of quality, or only for limited number of languages, text types or topics. However, customizing MT engines is difficult due to high cost, lack of the necessary language resources and not universally applicable tools and techniques.
Addressing the online language barriers requires action on various levels:
Interaction between the two programmes is close - H2020 will support and complement CEF by detecting and addressing gaps in machine translation coverage and quality, in real use situations.
The results will be robust, well-integrated and topically adapted machine translation, terminology processing, and other automated language processing facilities.