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Open Access 2023 | OriginalPaper | Buchkapitel

Deep Dive Machine Translation

verfasst von : Inguna Skadiņa, Andrejs Vasiḷjevs, Mārcis Pinnis, Aivars Bērziņš, Nora Aranberri, Joachim Van den Bogaert, Sally O’Connor, Mercedes García-Martínez, Iakes Goenaga, Jan Hajič, Manuel Herranz, Christian Lieske, Martin Popel, Maja Popović, Sheila Castilho, Federico Gaspari, Rudolf Rosa, Riccardo Superbo, Andy Way

Erschienen in: European Language Equality

Verlag: Springer International Publishing

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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 a0146pplied 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.

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Metadaten
Titel
Deep Dive Machine Translation
verfasst von
Inguna Skadiņa
Andrejs Vasiḷjevs
Mārcis Pinnis
Aivars Bērziņš
Nora Aranberri
Joachim Van den Bogaert
Sally O’Connor
Mercedes García-Martínez
Iakes Goenaga
Jan Hajič
Manuel Herranz
Christian Lieske
Martin Popel
Maja Popović
Sheila Castilho
Federico Gaspari
Rudolf Rosa
Riccardo Superbo
Andy Way
Copyright-Jahr
2023
DOI
https://doi.org/10.1007/978-3-031-28819-7_40

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