The European Commission has issued a call for tender, valued at EUR 2.4m (USD 2.6m), for a detailed study on the European language technologies market and the implementation of a service desk for the Connecting Europe Facility Automated Translation (CEF AT) platform.
The platform addresses connectivity and language barrier issues in the European Union in support of its vision for a Digital Single Market.
The tender, which is open until August 18, 2017, calls for developing the platform further to extend existing automated translation services in the EU and connect it with other cross-border and pan-European initiatives.
The EU wants CEF’s automated translation to become a ‘multilingualism enabler’ for CEF digital service infrastructures and stresses that this should go “beyond simple translation,” according to the tender document.
The first part of the project aims to assess the use of language technology services, including “identifying both supply and demand side of the market and potential gaps in the services provided by EU’s online machine translation service, MT@EC, and CEF eTranslation by public sector organizations and EU member states.”
“In the longer term, the results of the study shall contribute to the planning of the service portfolio development of the CEF AT platform and inform potential policy development activities,” the tender document further stated.
Hence, the contract will have two lots — Lot 1, valued at EUR 0.20m (USD), involves the language market study; and Lot 2, valued at EUR 2.2m (USD), involves the implementation of the ‘service desk’ part of the CEF AT, as well as program support action.
The contracts for Lot 1 will run for 14 months, while the contract for Lot 2 will be completed in about 40 months.
In January 2017, Slator reported results of another CEF AT call for tender, valued at EUR 5.8m, for projects that would improve the quality of machine translation services in the EU. Contracts have been awarded to seven vendors.
Back in May, the CEF program in the telecommunications sector also awarded EUR 6m in grants for six projects for automated translation, including a EUR 1.9m funding for a project to customize machine translation for public sector organizations.
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