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 |
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| container_title | Language resources and evaluation |
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| creator | Tiedemann, Jörg Aulamo, Mikko Bakshandaeva, Daria Boggia, Michele Grönroos, Stig-Arne Nieminen, Tommi Raganato, Alessandro Scherrer, Yves Vázquez, Raúl Virpioja, Sami |
| description | 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. |
| doi_str_mv | 10.1007/s10579-023-09704-w |
| format | Article |
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| source | Springer Nature - Complete Springer Journals |
| subjects | 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 |
| title | Democratizing neural machine translation with OPUS-MT |
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