European Language Equality : A Strategic Agenda for Digital Language Equality. Dieser Artikel ist nicht verfügbar.European Language Equality : A Strategic Agenda for Digital Language Equality

This open access book presents a comprehensive collection of the European Language Equality (ELE) project’s results, its strategic agenda and roadmap with key recommendations to the European Union on how to achieve digital language equality in Europe by 2030. The fabric of the EU linguistic landscape comprises 24 official languages and over 60 regional and minority languages. However, language barriers still hamper communication and the free flow of information. Multilingualism is a key cultural cornerstone of Europe, signifying what it means to be and to feel European. Various studies and resolutions have found a striking imbalance in the support of Europe’s languages through technologies, issuing a call to action. 

Following an introduction, the book is divided into two parts. The first part describes the state of the art of language technology and language-centric AI and the definition and metrics developed to measure digital language equality. It also presents the status quo in 2022/2023, i.e., the current level of technology support for over 30 European languages. The second part describes plans and recommendations on how to bring about digital language equality in Europe by 2030. It includes chapters on the setup and results of the community consultation process, four technical deep dives, an overview of existing strategic documents and an abridged version of the strategic agenda and roadmap.

The recommendations have been prepared jointly with the European community in the fields of language technology, natural language processing, and language-centric AI, as well as with representatives of relevant initiatives and associations, language communities and regional and minority language groups. Ensuring appropriate technology support for all European languages will not only create jobs, growth and opportunities in the digital single market. Overcoming language barriers in the digital environment is also essential for an inclusive society and for providing unity in diversity for many years to come.

Prof. Georg Rehm works as a Principal Researcher in the Speech and Language Technology Department of the German Research Center for Artificial Intelligence (DFKI) in Berlin. He is the Co-coordinator of the EU project European Language Equality (ELE) and was the Coordinator of the EU project European Language Grid (ELG). He has been involved as Coordinator or Principal Investigator in more than 20 large-scale research projects, including QURATOR, OpenGPT-X and NFDI for Data Science and AI. Prof. Rehm holds an MA in Computational Linguistics and Artificial Intelligence from the University of Osnabrück and a PhD in Computational Linguistics from the University of Gießen. He has authored, co-authored or edited around 200 research publications and organised more than 30 scientific events. In 2018, Prof. Rehm was awarded the honorary appointment as a DFKI Research Fellow for his outstanding scientific achievements. In 2021, he was appointed honorary professor for his outstanding achievements in research and education at Humboldt-Universität zu Berlin.

Prof. Andy Way is a Full Professor in the School of Computing at Dublin City University, and Deputy Director of ADAPT, the SFI-funded Centre for Digital Content Technology, in Dublin, having previously also been a director of the Centre for Next Generation Localisation (CNGL). Prof. Way has been the lead researcher on thirteen EU projects, including European Language Equality and SignON, and has published over 400 peer-reviewed papers. His research interests include all aspects of machine translation: statistical MT, example-based MT, neural MT, rule-based MT, hybrid models of MT, MT evaluation, teaching MT, etc. He was the recipient of the 2015 DCU President’s Research Award for Science and Engineering, and in 2019 received the prestigious Award of Honour from the International Association for Machine Translation.