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        Machine translation for everyone

        Empowering users in the age of artificial intelligence

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        Contributor(s)
        Kenny, Dorothy (editor)
        Collection
        Knowledge Unlatched (KU); KU Open Services
        Language
        English
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        Abstract
        Language learning and translation have always been complementary pillars of multilingualism in the European Union. Both have been affected by the increasing availability of machine translation (MT): language learners now make use of free online MT to help them both understand and produce texts in a second language, but there are fears that uninformed use of the technology could undermine effective language learning. At the same time, MT is promoted as a technology that will change the face of professional translation, but the technical opacity of contemporary approaches, and the legal and ethical issues they raise, can make the participation of human translators in contemporary MT workflows particularly complicated. Against this background, this book attempts to promote teaching and learning about MT among a broad range of readers, including language learners, language teachers, trainee translators, translation teachers, and professional translators. It presents a rationale for learning about MT, and provides both a basic introduction to contemporary machine-learning based MT, and a more advanced discussion of neural MT. It explores the ethical issues that increased use of MT raises, and provides advice on its application in language learning. It also shows how users can make the most of MT through pre-editing, post-editing and customization of the technology.
        URI
        https://library.oapen.org/handle/20.500.12657/61713
        Keywords
        Computers; Artificial Intelligence; Natural Language Processing
        DOI
        10.5281/zenodo.6653406
        ISBN
        9783961103485, 9783985540457
        Publisher
        Language Science Press
        Publisher website
        https://langsci-press.org/
        Publication date and place
        2022
        Grantor
        • Knowledge Unlatched
        Imprint
        Language Science Press
        Classification
        Natural language and machine translation
        Rights
        https://creativecommons.org/licenses/by/4.0/
        • Harvested from KU

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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