Machine Translation for MOOCs

By 2018 K4A will develop a high quality machine translation service and platform for all types of educational textual data available on a MOOC platform.

Developed via the TraMOOC project, the core of the service will be open-source and some premium add-on services (professional translation (PEMT) services, transcription/subtitling services for speech or support for additional target languages, and multilingual review services for students’ assignments by course domain experts speaking one of the target languages) are planned to be commercialised.

The service will support 11 target languages, 9 European and 2 BRIC. The open access will turn the MOOC translation service into a platform that will enable the integration of any MT solution in the educational domain, for any language. The service will be integrated, operated and field-tested in an actual MOOC platform (operational environment) and thus it will be developed to its full functionality (TRL 9).

European and world citizens have a need for access to open online education that is not constrained by language barriers. TraMOOC will create a translation service for MOOC educational data for 11 European and BRIC target languages.

  • MOOC providers need to offer high-quality, integrated multilingual educational services. TraMOOC will create a high quality translation service for MOOC textual data that is language independent in nature and addresses all types of MOOC text genre.
  • Machine Translation developers need a platform for promoting, testing and comparing their solutions. The TraMOOC translation service open-source platform will thus form a unified workbench for integrating MT solutions.
  • Language Technology Engineers need access to accurate and wide-coverage linguistic infrastructure, even for less widely spoken languages. The infrastructure exploitation, enrichment, and adaptation policy of TraMOOC, that focuses on bootstrapping, cross-language, and interdisciplinary approaches to create new or enrich/adapt available tools and resources, will provide the Language Technology community with infrastructure support and techniques to enhance it even for less richly equipped languages.