Open Journal Systems

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

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

Article ID: 2069
Vol 6, Issue 1, 2024, Article identifier:

VIEWS - 183 (Abstract) 55 (PDF)

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

Full Text:

PDF



References

Almahasees, Z. (2021). Machine translation evaluation and MT. Analysing English-Arabic Machine Translation, 9–48. https://doi.org/10.4324/9781003191018-2

Artamonova, M. V., Mambetov, A. A., & Tulina, E. V. (2023). Chatbot as a translation tool. Litera, 8, 235–253. https://doi.org/10.25136/2409-8698.2023.8.43875

Brownlee, J., Tam, A., Mayo, M., et al. (2023). Maximizing productivity with ChatGPT: Let generative AI help you work smarter. Machine Learning Mastery.

Chen, M. (2023). Correction: Trust, understanding, and machine translation: the task of translation and the responsibility of the translator. AI & SOCIETY. https://doi.org/10.1007/s00146-023-01696-z

Downie, J. (2019). Interpreters vs Machines. Routledge. https://doi.org/10.4324/9781003001805

Fan, P., Gong, H., & Gong, X. (2023). The Application of ChatGPT in Translation Teaching: Changes, Challenges, and Responses. International Journal of Education and Humanities, 11(2), 49–52. https://doi.org/10.54097/ijeh.v11i2.13530

Haleem, A., Javaid, M., & Singh, R. P. (2022). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(4), 100089. https://doi.org/10.1016/j.tbench.2023.100089

Hamilton, L., Elliott, D., Quick, A., et al. (2023). Exploring the Use of AI in Qualitative Analysis: A Comparative Study of Guaranteed Income Data. International Journal of Qualitative Methods, 22. https://doi.org/10.1177/16094069231201504

Khoshafah, F. (2023). ChatGPT for Arabic-English Translation: Evaluating the Accuracy. https://doi.org/10.21203/rs.3.rs-2814154/v1

Larroyed, A. (2023). Redefining Patent Translation: The Influence of ChatGPT and the Urgency to Align Patent Language Regimes in Europe with Progress in Translation Technology. GRUR International, 72(11), 1009–1017. https://doi.org/10.1093/grurint/ikad099

Lee, T. K. (2023). Artificial intelligence and posthumanist translation: ChatGPT versus the translator. Applied Linguistics Review, 0(0). https://doi.org/10.1515/applirev-2023-0122

Lu, Q., Qiu, B., Ding, L., et al. (2023). Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models: A Case Study on ChatGPT. https://doi.org/10.20944/preprints202303.0255.v1

Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003

Peng, K., Ding, L., Zhong, Q., et al. (2023). Towards Making the Most of ChatGPT for Machine Translation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4390455

Ruhmadi, A., & Al Farisi, M. Z. (2023). Morphological Error Analysis of Arabic-Indonesian Translation on ChatGPT (Indonesian). Aphorisme: Journal of Arabic Language, Literature, and Education, 4(1), 55–75. https://doi.org/10.37680/aphorisme.v4i1.3148

Sahari, Y., Al-Kadi, A. M. T., & Ali, J. K. M. (2023). A Cross Sectional Study of ChatGPT in Translation: Magnitude of Use, Attitudes, and Uncertainties. Journal of Psycholinguistic Research, 52(6), 2937–2954. https://doi.org/10.1007/s10936-023-10031-y

Sarrion, E. (2023). Using ChatGPT for text translation. Exploring the Power of ChatGPT, 107–116. https://doi.org/10.1007/978-1-4842-9529-8_12

Sarrion, E. (2023). Exploring the power of ChatGPT: Applications, techniques, and implications.

Si, C., Wu, K., Aw, A. T., et al. (2019). Sentiment Aware Neural Machine Translation. Proceedings of the 6th Workshop on Asian Translation. https://doi.org/10.18653/v1/d19-5227

Chia, C. E., & Liu, Y. L. (2022). Siri Buku Klasik Kesusasteraan Kanak-kanak Jilid Malaysia, 1st ed. Ningbo Publishing House.

Siu, S. C. (2023). ChatGPT and GPT-4 for Professional Translators: Exploring the Potential of Large Language Models in Translation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4448091

Siu, S. C. (2023). Revolutionizing Translation with AI: Unravelling Neural Machine Translation and Generative Pre-Trained Large Language Models. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4499768

Wu, J. (2023). A comparative analysis of Chinese-English translation quality based on ChatGPT: A case study of Chinese characteristic words. Journal of Social Science Humanities and Literature, 6(5), 53–58. https://doi.org/10.53469/jsshl.2023.06(05).08

Yilmaz, E. D., Naumovska, I., & Aggarwal, V. A. (2023). AI-Driven Labor Substitution: Evidence from Google Translate and ChatGPT. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4400516

Zhao, B., Jin, W., Del Ser, J., et al. (2023). ChatAgri: Exploring potentials of ChatGPT on cross-linguistic agricultural text classification. Neurocomputing, 557, 126708. https://doi.org/10.1016/j.neucom.2023.126708


DOI: https://doi.org/10.59400/fls.v6i1.2069
(183 Abstract Views, 55 PDF Downloads)

Refbacks

  • There are currently no refbacks.


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

License URL: http://creativecommons.org/licenses/by/4.0/