Comparing translation accuracy in Belt and Road Malaysia children's literature: Malay and Chinese native speakers vs ChatGPT

Authors

  • Yoke Lian Lau

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah
  • Zi Xian Yong

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah
  • Chen Eng Chia

    The Malaya Press, 1, Jalan TSB 10, Taman Perindustrian Sungai Buloh
  • Zi Hong Yong

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah
  • Anna Lynn Abu Bakar

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah
  • Chen Jung Ku

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah
  • Ernahwatikah Nasir

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah
  • Bavani Arumugam

    Centre for the Promotion of Knowledge and Language Learning, Universiti Malaysia Sabah

DOI:

https://doi.org/10.59400/fls.v6i1.2069

Abstract

The study investigates the translation processes of human and artificial intelligence translators in comparison. Human translators consist of a Chinese native speaker and belt and road translators. Different versions of artificial intelligence translators comprise ChatGPT 3.5 and ChatGPT 4.0. The research methodology employed is a keyword detection technique. One human translator and one translator powered by artificial intelligence achieved the highest scores in keyword detection, according to the results. Human translators continue to be indispensable in the field of translation, particularly in the translation of literary works. However, the research group is optimistic that artificial intelligence will soon be able to resolve this issue.

Keywords:

translator, Artificial Intelligent, publisher, Chinese, one belt and road

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Issue

Vol. 6 , Iss. 1 (March 2024)

Article Type

Article

License

Copyright © 2024 Yoke Lian Lau, Zi Xian Yong, Chen Eng Chia, Zi Hong Yong, Anna Lynn Abu Bakar, Chen Jung Ku, Ernahwatikah Nasir, Bavani Arumugam

Creative Commons License

This is an open access article under the Creative Commons Attribution 4.0 International License.