European Language Grid
The European cloud platform for Language Technology, Natural Language Processing and Language-centric AI
With 24 official EU and many more additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs), which are based on Natural Language Processing (NLP) and language-centric AI methods. The European LT industry landscape is dominated by thousands of SMEs and a few large players. Many are world-class, with technologies that outperform the dominant global enterprises. However, the European LT industry is also fragmented – by nation states, languages, verticals and sectors. Likewise, while much of European LT research is world-class, with results transferred into industry and commercial products, its full impact is held back by fragmentation. The EU-funded project European Language Grid (ELG) addresses this fragmentation by establishing the ELG as the primary platform for LT in Europe. The ELG is a scalable cloud platform, providing, in an easy-to-integrate way, access to hundreds of commercial and non-commercial Language Technologies for all European languages, including running NLP tools and services as well as data sets and resources. It enables the commercial and non-commercial European LT community to deposit and upload their technologies and data sets into the ELG, to deploy them through the grid, and to connect with other resources. The ELG will ultimately boost the Multilingual Digital Single Market towards a thriving European LT community, creating new jobs and opportunities. Through two open calls, 15 pilot projects are financially supported, extending the ELG portfolio and demonstrating its usefulness. ELG fosters “language technologies for Europe built in Europe”, tailored to our languages and cultures and to our societal and economical demands, benefitting the European citizen, society, innovation and industry. The presentation will provide a comprehensive overview of the ELG project and cloud platform including a short demo of the current version of the system. In addition, the recently started EU sister project ELE (European Language Equality) will be briefly introduced. With a consortium of 53 partners, the ELE project develops a strategic agenda and roadmap for achieving full digital language equality in Europe by 2030.
Dr. Georg Rehm works as a Principal Researcher in the Speech and Language Technology Lab at the German Research Center for Artificial Intelligence (DFKI), in Berlin. He’s the General Secretary of META-NET, an EU/EC-funded Network of Excellence dedicated to building the technological foundations of a multilingual European information society. Georg Rehm is the Coordinator of the EU-funded project European Language Grid (ELG, 2019-2022) and the BMBF-funded project QURATOR (Curation Technologies, 2018-2021). Furthermore, he is the Co-coordinator of the EU project European Language Equality (ELE, 2021-2022) and active in the EU project Lynx: Building the Legal Knowledge Graph for Smart Compliance Services in Multilingual Europe (2017-2021), in the EU project HumanE-AI-Net (2020-2023), in the BMWi-funded project SPEAKER (2020-2023) and a number of other projects. In 2018, Georg Rehm was awarded the honorary appointment as a DFKI Research Fellow for outstanding scientific achievements and special accomplishments in technology transfer. Since 2013, Georg Rehm has been the Head of the German/Austrian Chapter of the World Wide Web Consortium (W3C), hosted at DFKI in Berlin. Also related to ICT and standardisation, Georg Rehm is a member of the DIN Presidential Committee FOCUS.ICT. In the 2021/2022 term, Georg Rehm serves as the Secretary of the European Chapter of the Association for Computational Linguistics (EACL). Georg Rehm holds an M.A. in Computational Linguistics and Artificial Intelligence, Linguistics and Computer Science from the University of Osnabrück and a PhD in Computational Linguistics from the University of Gießen. He has authored, co-authored or edited approx. 200 research publications.