Cross-Lingual Embeddings for Less-Represented Languages in European News Media

akronüüm: EMBEDDIA
algus: 2019-01-01
lõpp: 2021-12-31
 
programm: H2020 - Horisont 2020
alaprogramm: LEIT - Juhtkoht tööstustehnoloogias
instrument: RIA
projektikonkurss: H2020-ICT-2018-2
projekti number: 825153
kestus kuudes: 36
partnerite arv: 10
 
lühikokkuvõte: Access to the internet is no longer a luxury---it is a basic component of everyday life and civic engagement, but one in which language continues to be a challenge for fair and equitable access. As Europe becomes more multicultural, and personal and professional mobility between cultures rapidly increases, access to fundamental resources such as local news and government services is limited by the great diversity of the EU's 37 languages. The internet mostly developed in English, and without clear planning for how language issues might form barriers to access and engagement, nor how multilingualism might be supported. In the EU, websites and online services for citizens have developed national local language resources, and often only provide a second language (usually English) when absolutely needed; but the great proliferation of web content, multiple and fast-changing content streams, and an expanding user interest base make this approach untenable. And while advanced natural language research and resources exist for a few dominant languages (English, French, German), many of Europe's smaller language communities---and the news media industry that serves them---lack appropriate tools for multilingual internet development. For the EU to realise a truly equitable, open, multilingual future internet, new tools allowing high quality transformations (not translations) between languages are urgently needed. The EMBEDDIA project seeks to address these challenges by leveraging innovations in the use of cross-lingual embeddings coupled with deep neural networks to allow existing monolingual resources to be used across languages, leveraging their high speed of operation for near real-time applications, without the need for large computational resources. Across three years, the project's six academic and four industry partners will develop novel solutions including for under-represented languages, and test them in real-world news and media production contexts.
partneri jrk nr ja roll partneri nimi riik kontaktisik koduleht
1 koordinaator INSTITUT JOZEF STEFAN SI Senja POLLAK www.ijs.si
2 partner QUEEN MARY UNIVERSITY OF LONDON UK http://www.qmul.ac.uk
3 partner UNIVERZA V LJUBLJANI SI http://www.uni-lj.si
4 partner UNIVERSITE DE LA ROCHELLE FR www.univ-lr.fr
5 partner HELSINGIN YLIOPISTO FI www.helsinki.fi
6 partner THE UNIVERSITY OF EDINBURGH UK www.ed.ac.uk
7 partner TEXTA OÜ EE www.texta.ee
8 partner AS EKSPRESS MEEDIA EE http://www.ekspressmeedia.ee/
9 partner STYRIA MEDIJSKI SERVISI DOO ZA TRGOVINU I USLUGE HR www.styria.ai
10 partner OY SUOMEN TIETOTOIMISTO - FINSKA NOTISBYRAN AB FI www.stt.fi