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Journal of Humanities, Arts and Social Science

ISSN Print: 2576-0556 Downloads: 472837 Total View: 3629540
Frequency: monthly ISSN Online: 2576-0548 CODEN: JHASAY
Email: jhass@hillpublisher.com
Article Open Access http://dx.doi.org/10.26855/jhass.2024.11.023

On the Role of Expertise in Applying MTPE Mode in Medical Translation

Jing Ning1,*, Shiyang Ran2

1School of Foreign Studies, Southern Medical University, Guangzhou 510515, Guangdong, China.

2Institute of Contemporary China Studies, Sichuan International Studies University (SISU), Chongqing 400031, China.

*Corresponding author: Jing Ning

Published: December 18,2024

Abstract

With the continuous development of neural network technology and AI translation in specialized fields, machine translation + post-editing (MTPE) has become the predominant mode of translation practice. Medical texts are often complex, containing specialized terminology, nuanced language, and context-specific information that require a deep understanding of both the source and target languages. Expertise in the field ensures that translators can effectively assess and refine the machine-generated translations, and correct inaccuracies thus ensuring a quality output. This paper first reviews the literature on the application of the MTPE mode to specialized texts. Then, it summarizes four types of mistranslation based on translation practice, namely inaccuracies, unprofessionalism, redundancy, nonfluency, inconsistency, inconherency, and incompleteness. Furthermore, case analyses at the lexical, sentence, and discourse levels are illustrated to discuss the collaboration between machine translation and human editing. The study emphasizes the need to enhance the adaptability of neural machine translation models in specialized fields, while human translators should also continually enhance their specialized language skills and solidify their domain knowledge base to effectively carry out post-editing, proofreading, and modifications.

References

Álvarez-Vidal, S., Oliver, A., & Badia, T. (2021). What do post-editors correct? A fine-grained analysis of SMT and NMT errors. Tradumàtica Tecnologies de la Traducció, 19, 131-147. https://doi.org/10.5565/rev/tradumatica.286.

Arenas, A. G., Moorkens, J., & Orrego-Carmona, D. (2024). “A Spanish version of EastEnders”: A reception study of a telenovela subtitled using MT. Jostrans—The Journal of Specialised Translation, 41, 230-254.

https://doi.org/10.26034/cm.jostrans.2024.4724.

Arenas, A. G., Valdez, S., & Dorst, A. G. (2024). Does training in post-editing affect creativity? Jostrans—The Journal of Specialised Translation, 41, 74-97. https://doi.org/10.26034/cm.jostrans.2024.4712.

Dai, G. R., & Liu, S. Q. (2023). Neural machine translation: Progress and challenges. Foreign Language Teaching, 44(01), 82-89.

Koehn, P. (2020). Neural machine translation. Cambridge University Press. https://doi.org/10.1017/9781108608480.

O’Brien, S. (2002). Teaching post-editing: A proposal for course content. In Proceedings of the 6th EAMT workshop: Teaching machine translation.

Pérez, C. R. (2024). Re-thinking machine translation post-editing guidelines. Jostrans—The Journal of Specialised Translation, 41, 26-47. https://doi.org/10.26034/cm.jostrans.2024.4696.

Summer, L., Li, Y. M., & Li, H. W. (2022). Machine translation and post-editing of scientific paper abstracts in the context of artificial intelligence. Journal of Editing, 34(04), 396-401, 406.

Tan, X. (2021). Post-editing of machine translation for medical texts: A translation practice report (Master's thesis). Central University for Nationalities.

Tang, B., & Chen, S. (2020). Evaluation of online machine translation software for medical text translation. Chinese Science and Technology Translation, 33(03), 23-26, 49.

Wei, Y., Li, N., & Zhao, L. W. (2022). A study on the quality of machine translation, common error types, and countermeasures: Based on the history of machine translation development. Modern Linguistics, 10, 1944.

https://doi.org/10.12677/ML.2022.109261.

Wu, Q. G., & Li, J. W. (2016). A study on the post-editing model of news translation. Foreign Language Electrification Teaching, 06, 74-79.

Xiang, L., & Li, Y. M. (2014). The current status and prospects of machine translation and translation technology research: An interview with Bernard Marc Sartre-Worth. Chinese Science and Technology Translation, 27(1), 24-27.

Yang, W. D., & Fan, Z. R. (2021). A case study of post-editing in scientific discourse machine translation. Shanghai Translation, 06, 54-59.

Zhang, F. L. (2020). A preliminary discussion on machine translation technology in legal translation. Foreign Language Electrification Teaching, 01, 53-58, 8.

Zhuang, X. (2014). On post-editing of machine translation. Chinese Translation, 35(06), 68-73.

How to cite this paper

On the Role of Expertise in Applying MTPE Mode in Medical Translation

How to cite this paper: Jing Ning, Shiyang Ran. (2024) On the Role of Expertise in Applying MTPE Mode in Medical Translation. Journal of Humanities, Arts and Social Science8(11), 2595-2604.

DOI: http://dx.doi.org/10.26855/jhass.2024.11.023