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Loboda, Krzysztof; Mastela, Olga – Interpreter and Translator Trainer, 2023
Mass adoption of neural machine translation (NMT) tools in the translation workflow has exerted a significant impact on the language services industry over the last decade. There are claims that with the advent of NMT, automated translation has reached human parity for translating news (see, e.g. Popel et al. 2020). Moreover, some machine…
Descriptors: Computer Software, Computational Linguistics, Polish, Folk Culture
Dubeda, Tomáš; Obdržálková, Vanda – Interpreter and Translator Trainer, 2021
We examine the stylistic aspects of L2 translations using a set of quantifiable descriptors. The sample includes 40 translations of a promotional text from Czech into English and French produced by novices and professional translators. The general stylistic competence is slightly higher in the group of professionals, although the overall quality…
Descriptors: Translation, Language Styles, Language Processing, Second Languages
What to Expect from Neural Machine Translation: A Practical In-Class Translation Evaluation Exercise
Moorkens, Joss – Interpreter and Translator Trainer, 2018
Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…
Descriptors: Translation, Teaching Methods, Computational Linguistics, Quality Assurance