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http://dx.doi.org/10.15207/JKCS.2020.11.6.281

Study on Translators' Acceptance of Machine Translation  

Chun, Jong-Sung (Department of Journalism and Mass Communication, Hanyang University)
Publication Information
Journal of the Korea Convergence Society / v.11, no.6, 2020 , pp. 281-288 More about this Journal
Abstract
This study delves into acceptance on neural network machine translation (NMT) such as Google Translate and Papago that uses technical acceptance model. In conclusion, it turned out that perceived usefulness impacts translators' attitude towards NMT. In other words, if translators determine that NMT is related to their work and the quality of the deliverables is guaranteed, they were more positive towards it. Unlike the existing normative approach that translators feel threatened by NMT, empirical results tell us translators perceive NMT as a business tool and such perception was largely influenced by advices of their colleagues and friends and expectations for use.
Keywords
Neural network; Machine translation; NMT; TAM; Translator;
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