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20 octobre 2022
- doi: 10.4000/books.aaccademia.11077
- eisbn: 9791280136947
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
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linguistica computazionale linguistica linguistique computationelle linguistique Computational Linguistics Language Linguistics LAN009000 Linguistics CFSujets proches
Learning, Machine Linguistic science Science of languageCiter ce document
Mauro Cettolo et al., « On the Development of Customized Neural Machine Translation Models », Accademia University Press, ID : 10.4000/books.aaccademia.11077
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Résumé
Recent advances in neural modeling boosted performance of many machine learning applications. Training neural net-works requires large amounts of clean data, which are rarely available; many methods have been designed and inves-tigated by researchers to tackle this is-sue. As a partner of a project, we were asked to build translation engines for the weather forecast domain, relying on few, noisy data. Step by step, we developed neural translation models, which outper-form by far Google Translate. This paper details our approach, that - we think - is paradigmatic for a broader category of applications of machine learning, and as such could be of widespread utility.