Work

Global Under-Resourced Media Translation (GoURMET)

Year: 2019

Type: conference-paper

Abstract: We present the EU H2020 GoURMET project (2019-2021) which aims to tackle the challenge of low-resource machine translation for our media partners. This will help them to both monitor news in a wider range of languages, and also more efficiently produce content especially for languages from Africa and India.

Source: Edinburgh Research Explorer (University of Edinburgh)

Authors: Birch, Alexandra, Haddow, Barry; id_orcid 0009-0008-1295-8888, Titov, Ivan, Miceli Barone, Antonio Valerio, Bawden, Rachel, Sánchez-Martinez, Felipe, Forcada, Mikel L., Esplà-Gomis, Miquel, Sánchez-Cartagena, Victor M., Pérez-Ortiz, Juan Antonio, Aziz, Wilker, Secker, Andrew, van der Kreeft, Peggy

Institutions: University of Alicante, University of Amsterdam, British Broadcasting Corporation (United Kingdom), Deutsche Welle

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDGs: Partnerships for the goals, Reduced inequalities

Open Access status: green

Funder: European Commission

Award: Global Under-Resourced MEedia Translation

OpenAlex ID: W2978206402

FWCI: 0.571

Cites:

Cited by: 9

Related to: 10