Democratizing neural machine translation with OPUS-MT

Democratizing neural machine translation with OPUS-MT

This paper presents the OPUS ecosystem with a focus on the development of open machine translation models and tools, and their integration into end-user applications, development platforms and professional workflows. We discuss our ongoing mission of increasing language coverage and translation qual...

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Veröffentlicht in:Language resources and evaluation 2024-06, Vol.58 (2), p.713-755
Hauptverfasser: Tiedemann, Jörg, Aulamo, Mikko, Bakshandaeva, Daria, Boggia, Michele, Grönroos, Stig-Arne, Nieminen, Tommi, Raganato, Alessandro, Scherrer, Yves, Vázquez, Raúl, Virpioja, Sami
Format: Artikel
Sprache:eng
Schlagworte:
Computational Linguistics
Computer Science
Datasets
Deep learning
Energy consumption
Language
Language and Literature
Linguistics
Machine translation
Natural language processing
Open data
Original Paper
Social Sciences
Software
Translations
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Beschreibung
Zusammenfassung:This paper presents the OPUS ecosystem with a focus on the development of open machine translation models and tools, and their integration into end-user applications, development platforms and professional workflows. We discuss our ongoing mission of increasing language coverage and translation quality, and also describe work on the development of modular translation models and speed-optimized compact solutions for real-time translation on regular desktops and small devices.
ISSN:1574-020X
1574-0218
DOI:10.1007/s10579-023-09704-w