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BuchGebunden
248 Seiten
Englisch
Taylor & Franciserschienen am29.08.2024
This book, authored by leading experts, demystifies machine translation, explaining its origins, its training data, how neural machine translation and LLMs work, how to measure their quality, how translators interact with contemporary systems for automating translation, and how readers can build their own machine translation or LLM.mehr
Verfügbare Formate
BuchGebunden
EUR172,50
TaschenbuchKartoniert, Paperback
EUR48,00
E-BookEPUB0 - No protectionE-Book
EUR47,49
E-BookPDF0 - No protectionE-Book
EUR47,49

Produkt

KlappentextThis book, authored by leading experts, demystifies machine translation, explaining its origins, its training data, how neural machine translation and LLMs work, how to measure their quality, how translators interact with contemporary systems for automating translation, and how readers can build their own machine translation or LLM.
Details
ISBN/GTIN978-1-032-46352-0
ProduktartBuch
EinbandartGebunden
FormatGenäht
Erscheinungsjahr2024
Erscheinungsdatum29.08.2024
Seiten248 Seiten
SpracheEnglisch
MasseBreite 156 mm, Höhe 234 mm, Dicke 16 mm
Gewicht558 g
Artikel-Nr.61443328

Inhalt/Kritik

Inhaltsverzeichnis
ContentsSeries Editor´s ForewordPrefaceAbbreviations and AcronymsChapter 1 - The Roots of Machine TranslationChapter 2 - Data for Machine TranslationChapter 3 - Translation Memory and Computer-Assisted Translation toolsChapter 4 - Neural Networks and Neural Machine TranslationChapter 5 - Machine Translation EvaluationChapter 6 - Neural Machine Translation: Build or Buy?Chapter 7 - Building Machine Translation Models with ColabChapter 8 - Machine Translation Post-EditingChapter 9 - Machine Translation in Multimedia Translation and LocalisationChapter 10 - Large Language Models and Multilingual Language Models: The Future of Machine Translation?Chapter 11 - Sociotechnical Effects of Machine TranslationAfterwordGlossarymehr

Autor

Joss Moorkens is Associate Professor at the School of Applied Language and Intercultural Studies and Science Lead at the ADAPT Centre at Dublin City University, Ireland. He is General Co- Editor of the journal Translation Spaces, author and editor of several books, articles, chapters, and special issues on translation technology, and sits on the board of the European Masters in Translation network.

Andy Way is Professor of Computing and Co- Founder of the ADAPT Centre at Dublin City University, Ireland. He was previously editor of the Machine Translation journal for 15 years, and president of both the European and International Associations for Machine Translation. He has over 450 publications, including five books on machine translation.

Séamus Lankford is a Computer Science lecturer with over 25 years' experience at the Munster Technological University, Ireland. He has published extensively on the topic of machine translation. The focus of his doctoral thesis was the enhancement of NMT of low- resource languages through corpus development, human evaluation, and explainable AI architectures.
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