TY - GEN
T1 - Observatory for Language Resources and Machine Translation in Europe – LT_Observatory
AU - Maegaard, Bente
AU - Povlsen, Claus
AU - Olsen, Sussi
AU - Henriksen, Lina
AU - Mazura, Margaretha
AU - Lusicky, Vesna
AU - Budin, Gerhard
AU - Rodríguez, Blanca
AU - Esparza, Luz
PY - 2017
Y1 - 2017
N2 - The European Digital Single Market, one of the main goals of Europe 2020, is still fragmented due to language barriers. Language technologies (LT), like Machine Translation (MT) solutions, are key elements for solving this fragmentation. Nevertheless, it is necessary to compile, benchmark the quality and facilitate the access to Language Resources to build successful MT solutions. With these aims, the LT_Observatory project has been developed (2014–2016). The project was funded by the European Commission through the H2020 programme. This article describes the main outputs: An on-line catalogue of language resources in existing pools and other national resources based on pre-identified user needs.Methodologies for improving the quality and usability of language resources.National and regional language strategies, policies and funding sources to support language technologies.An EcoGuide that aims to adapt the findings of the LT_Observatory project for various stakeholder groups providing practical information for operational usability of LRs and tools for MT application, funding opportunities, and recommendations geared at European, national and regional policy and decision makers. This project has been carried out by a team of five EU partners with complementary expertise: ZABALA (EU project management and community engagement), EMF (European Multimedia Forum with experience in outreach/social media, and funding, e.g. ESIF and combined funding), LT Innovate (the Language Technology Industry Association), CLARIN ERIC (LT resources and infrastructure, including a Virtual Language Observatory), and University of Vienna/InfoTerm (international information centre for terminology).
AB - The European Digital Single Market, one of the main goals of Europe 2020, is still fragmented due to language barriers. Language technologies (LT), like Machine Translation (MT) solutions, are key elements for solving this fragmentation. Nevertheless, it is necessary to compile, benchmark the quality and facilitate the access to Language Resources to build successful MT solutions. With these aims, the LT_Observatory project has been developed (2014–2016). The project was funded by the European Commission through the H2020 programme. This article describes the main outputs: An on-line catalogue of language resources in existing pools and other national resources based on pre-identified user needs.Methodologies for improving the quality and usability of language resources.National and regional language strategies, policies and funding sources to support language technologies.An EcoGuide that aims to adapt the findings of the LT_Observatory project for various stakeholder groups providing practical information for operational usability of LRs and tools for MT application, funding opportunities, and recommendations geared at European, national and regional policy and decision makers. This project has been carried out by a team of five EU partners with complementary expertise: ZABALA (EU project management and community engagement), EMF (European Multimedia Forum with experience in outreach/social media, and funding, e.g. ESIF and combined funding), LT Innovate (the Language Technology Industry Association), CLARIN ERIC (LT resources and infrastructure, including a Virtual Language Observatory), and University of Vienna/InfoTerm (international information centre for terminology).
KW - Faculty of Humanities
M3 - Article in proceedings
SN - ISBN 978-3-319-69364-4
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 20
EP - 37
BT - Future and Emerging Trends in Language Technology
A2 - Quesada, José F.
A2 - López-Soto, Teresa
A2 - Martín Mateos, Francisco J.
PB - Springer
ER -