Research Article

Man vs Machine: A Comparison of Linguistic, Cultural, and Stylistic Levels in Literary Translation

Authors

  • Mohammed Juma Zagood PhD in Translation Studies, Assistant Professor, Department of Languages and Literature, UAE University, UAE & Department of English, El-Mergib University, Libya
  • Alya Al-Nuaimi Undergraduate Student, Department of Languages and Literature, UAE University, UAE
  • Aysha Al-Blooshi Undergraduate Student, Department of Languages and Literature, UAE University, UAE

Abstract

This study aims to remark the differences between human translation (HT) and machine translation (MT) on linguistic, cultural, and stylistic levels when translating English literary texts into Arabic. To accomplish the goal of this study, a comparison between the Arabic HT and MT of Saki’s (1914) short story ‘The Open Window’ is conducted. The study focuses on comparing the two translations (HT and MT) on linguistic, cultural, and stylistic levels to identify the differences between HT and MT in translating literary texts. Throughout this comparison, it is found out that both HT and MT have their advantages and disadvantages on different levels. It has also been found out that MT is unable to identify cultural items and consequently mistranslate them. It is, therefore, concluded that MT can work proficiently on certain levels besides the intervention of the human mind. The findings of this study provide translators using MT with a clear vision on the points of strength and weaknesses in translating literary texts. 

Article information

Journal

International Journal of Linguistics, Literature and Translation

Volume (Issue)

4 (2)

Pages

70-77

Published

2021-02-27

How to Cite

Zagood , M. J. ., Al-Nuaimi , A. ., & Al-Blooshi , A. . (2021). Man vs Machine: A Comparison of Linguistic, Cultural, and Stylistic Levels in Literary Translation. International Journal of Linguistics, Literature and Translation, 4(2), 70–77. https://doi.org/10.32996/ijllt.2021.4.2.10

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Keywords:

Culture, Human Translation, Linguistics, Machine Translation, Style