Differentiating between machine translation and student translation: red flags and salient lexicogrammatical features.

Andrew Richard Burns Innes

Abstract


ABSTRACT

Machine translation enables students to produce work in the target L2 which may be superior to that which they could produce otherwise.  The present study examines whether use of machine translation can be detected by teachers.  Seventeen native teachers compared and assessed the authorship of five human translations (HT) and five machine translations (MT) of Japanese news stories.  Native teachers were able to accurately detect the difference in 74.04% of cases due to increased passive clauses (a ratio of 1 to 2.5), and inappropriate pronoun use (a ratio of 1 to 6.5) when MT was used.

 


Keywords


SFL, machine translation, detection, student essays.

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References


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DOI: http://dx.doi.org/10.17951/lsmll.2019.43.4.1-13
Data publikacji: 2019-12-30 00:00:00
Data złożenia artykułu: 2019-05-14 11:55:12


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