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Deep dive machine translation

Skadiņa, Inguna orcid logoORCID: 0000-0003-4787-7099, Vasiḷjevs, Andrejs orcid logoORCID: 0000-0002-5029-0697, Pinnis, Mārcis orcid logoORCID: 0000-0001-6832-5600, Bērziņš, Aivars orcid logoORCID: 0000-0003-2933-3709, Aranberri, Nora orcid logoORCID: 0000-0003-3719-9167, Van den Bogaert, Joachim, O'Connor, Sally, García-Martínez, Mercedes, Goenaga, Iakes orcid logoORCID: 0000-0002-0946-5782, Hajič, Jan orcid logoORCID: 0000-0002-3503-7730, Herranz, Manuel, Lieske, Christian, Popel, Martin orcid logoORCID: 0000-0002-3628-8419, Popović, Maja orcid logoORCID: 0000-0001-8234-8745, Castilho, Sheila orcid logoORCID: 0000-0002-8416-6555, Gaspari, Federico orcid logoORCID: 0000-0003-3808-8418, Rosa, Rudolf, Superbo, Riccardo and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2023) Deep dive machine translation. In: Rehm, Georg orcid logoORCID: 0000-0002-7800-1893 and Way, Andy orcid logoORCID: 0000-0001-5736-5930, (eds.) European Language Equality A Strategic Agenda for Digital Language Equality. Cognitive Technologies (COGTECH) . Springer, Berlin, pp. 263-287. ISBN 978-3-031-28819-7

Abstract
Machine Translation (MT) is one of the oldest language technologies having been researched for more than 70 years. However, it is only during the last decade that it has been widely accepted by the general public, to the point where in many cases it has become an indispensable tool for the global community, supporting communication between nations and lowering language barriers. Still, there remain major gaps in the technology that need addressing before it can be successfully applied in under-resourced settings, can understand context and use world knowledge. This chapter provides an overview of the current state-of-the-art in the field of MT, offers technical and scientific forecasting for 2030, and provides recommendations for the advancement of MT as a critical technology if the goal of digital language equality in Europe is to be achieved.
Metadata
Item Type:Book Section
Refereed:Yes
Subjects:Computer Science > Artificial intelligence
Humanities > Language
Humanities > Translating and interpreting
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Publisher:Springer
Official URL:https://doi.org/10.1007/978-3-031-28819-7_40
Copyright Information:© 2023 The Authors
Funders:The European Language Equality project has received funding from the European Union under the grant agreement no. LC-01641480 – 101018166 (ELE).
ID Code:28380
Deposited On:07 Jul 2023 15:28 by Federico Gaspari . Last Modified 11 Jul 2023 14:18
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