Challenge

There is a continuing increasing need for educational institutes to provide course syllabi documentation and other educational information in English. Access to translated course syllabi and degree programmes plays a crucial role in the degree to which universities effectively attract foreign students and, more importantly, has an impact on international profiling.

Due to budget and time constraints, a large amount of syllabi and study programmes end up being published in the local language only and translated versions are never made available.

The Bologna Translation Service aims to overcome these problems by providing a low-cost, web-based, high-quality machine translation (MT) service. The service will be accessible through a web-interface and will expose a web services API providing connectivity to universities’ local content repositories where course syllabi and degree programmes are produced and edited.

Impact

By making use of customisation, integration and validation techniques to improve the quality output of MT, the Bologna Translation Service will allow citizens, institutions and businesses, to get access to university study programmes previously unknown to them. The Bologna Translation Service will help to increase student mobility. This service will play a role in making degrees, qualifications and awards visible to the labour market, identifying career opportunities and stimulating the research needed to increase European competitiveness. These principles have been clearly identified by the European Commission in the Sorbonne and Bologna Declarations, Lisbon Strategy and the Modernisation Agenda.

Innovation

The Bologna Translation Service will build a highly specialised domain-focused automated translation service that integrates typologically different MT technologies with translation memory (TM) technology making use of automated post-editing (PE) techniques into a web-based collaboration platform.

The project will cover 9 languages including Chinese, Dutch, English, Finnish, French, German, Portuguese, Spanish and Turkish.

Cross Language contributes its web-based collaboration framework to the project as well as its MT evaluation expertise. Convertus brings its experience and technology from a high-quality machine translation service in use by several Swedish universities. Traslán provides solid experience with statistical MT including hierarchical techniques. The project takes advantage of Koç university’s competence in Turkish. Rule-based MT expertise is supplied by Eleka.

In addition the consortium intends to collaborate closely with its User Group consisting of ten universities at project start, providing valuable user feedback.

• Hogeschool Gent, Belgium
• Vrije Universiteit Amsterdam, Holland
• Université Charles-de-Gaulle, Lille III, France
• University of Tampere, Finland
• Aalto University, Finland
• University of Evora, Portugal 
• Minho University, Portugal 
• Koç University, Turkey
• Kocaeli University, Turkey
• University of Saarland, Germany

The consortium is continuously looking to expand its User Group. If you are interested in joining, please fill out the registration form.