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Adapting NMT to caption translation in Wikimedia Commons for low-resource languages

Poncelas, Alberto orcid logoORCID: 0000-0002-5089-1687, Sarasola, Kepa orcid logoORCID: 0000-0003-4349-6088, Dowling, Meghan orcid logoORCID: 0000-0003-1637-4923, Way, Andy orcid logoORCID: 0000-0001-5736-5930, Labaka, Gorka orcid logoORCID: 0000-0003-4611-2502 and Alegria, Iñaki orcid logoORCID: 0000-0002-0272-1472 (2019) Adapting NMT to caption translation in Wikimedia Commons for low-resource languages. Procesamiento de Lenguaje Natural, 63 . pp. 33-40. ISSN 1135-5948

Abstract
This paper presents a successful domain adaptation of a general neural machine translation (NMT) system using a bilingual corpus created with captions for images in Wikimedia Commons for the Spanish-Basque and English-Irish pairs.
Metadata
Item Type:Article (Published)
Refereed:Yes
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Publisher:Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN)
Official URL:http://journal.sepln.org/sepln/ojs/ojs/index.php/p...
Copyright Information:© 2019 Sociedad Española para el Procesamiento del Lenguaje Natural
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:TADEEP project (Spanish Ministry of Economy and Competitiveness TIN2015- 70214-P, with FEDER funding), ADAPT Centre for Digital Content Technology under the SFI (Grant 13/RC/2106), European Regional Development Fund
ID Code:24603
Deposited On:15 Jun 2020 13:43 by Vidatum Academic . Last Modified 25 Jun 2021 13:02
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