Neural Machine Translations of Thai Culturally Specific Items into English: Audiovisual Text Experimented
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Abstract
This study investigates the efficiency of three Neural Machine Translation (NMT) tools—Google Translate, Microsoft Bing, and Amazon Translate—in rendering culturally specific items (CSIs) at both lexical and sentential levels. Five CSIs, mae ya nang (แม่ย่านาง), lek lai (เหล็กไหล), ruesi (ฤาษี), pha yan (ผ้ายันต์) and palat khik (ปลัดขิก), from a selected Thai commercial, were categorised by Katan’s ‘Triad of Culture’ framework. A synthesized typology based on Dickins’s conceptual grid was employed to analyse the translation procedures of each NMT service. The FAR model proposed by Pedersen is employed to assess the subtitle quality. The selected segment of an audiovisual text from a Thai auto insurance commercial was input into the NMT services to evaluate their ability to enhance translation efficiency and quality. The findings revealed that the technical cultural frame predominantly influenced the NMT services, resulting in the focus on linguistic transfer over interpretation. At the lexical level, the NMT tools employed an exoticising strategy, resulting in the translations that were primarily oriented towards the source culture and the source language. At the sentential level, the performance of NMT systems deteriorated, with several mistranslations identified, though omission errors were not present. The outputs also lacked fluency, necessitating post-editing. Despite literature suggesting improvements in NMT output quality, these NMT engines have yet to significantly impact professional translation for the Thai-English language pair. For low-resource languages such as Thai, the role of the human translator remains indispensable and cannot be fully replicated by current machine translation systems.
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References
Almahasees, Z. M. (2018). Assessment of Google and Microsoft Bing translation of journalistic texts. International Journal of Languages, Literature and Linguistics, 4(3), 231–235. https://doi.org/10.18178/IJLLL.2018.4.3.178
Amazon Web Services. (n.d.). Amazon translate FAQs. Retrieved October 6, 2024, from https://aws.amazon.com/translate/faqs/
Bowker, L., & Fisher, D. (2010). Computer-aided translation. In Y. Gambier & L. van Doorslaer (Eds.), Handbook of translation studies (Vol. 1, pp. 60–65). John Benjamins.
Castilho, S., Moorkens, J., Gaspari, F., Calixto, I., Tinsley, J., & Way, A. (2017). Is neural machine translation the new state of the art? The Prague Bulletin of Mathematical Linguistics, 108, 109–120. https://doi.org/10.1515/pralin-2017-0013
Castilho, S., Moorkens, J., Gaspari, F., Sennrich, R., Way, A., & Georgakopoulou, P. (2018). Evaluating MT for massive open online courses. Machine Translation, 32(3), 255–278. https://doi.org/10.1007/s10590-018-9221-y
DeepL. (n.d.). About DeepL language models. Retrieved April 11, 2026, from https://support.deepl.com/hc/en-us/articles/14241705319580-About-DeepL-language-models#h_01JCNJ5K0A7A62EWGDRQSQY071
Dickins, J. (2012). The translation of culturally specific items. In A. Littlejohn & S. R. Mehta (Eds.), Language studies: Stretching the boundaries (pp. 43–60). Cambridge Scholars Publishing.
ERGO Insurance Thailand. (2022, March 26). Saksit di krap [Your magical powers are real!] [Video]. YouTube. https://www.youtube.com/watch?v=i_8ifT27xxw
Forcada, M. L. (2010). Machine translation today. In Y. Gambier & L. van Doorslaer (Eds.), Handbook of translation studies (Vol. 1, pp. 215–223). John Benjamins.
Forcada, M. L. (2017). Making sense of neural machine translation. Translation Spaces, 6(2), 291–309. https://doi.org/10.1075/ts.6.2.06for
Google Cloud. (n.d.). Neural Machine Translation model. Retrieved October 6, 2024, from https://cloud.google.com/translate/docs/languages
Hall, E. T. (1959). The silent language. Doubleday.
Hervey, S., & Higgins, I. (2002). Thinking French translation (2nd ed.). Routledge.
Intarawut, P. (1999). Siwalueng nai phak tai [Phallic amulet in the south]. In Saranukrom watthanatham thai phak tai [Encyclopedia of southern Thai culture] (Vol. 15, pp. 7500–7518). Thai Culture Encyclopedia Foundation, Siam Commercial Bank.
ITVX. (2023, February 17). John Torode’s Friday night pad thai. This Morning. https://www.itv.com/thismorning/articles/john-torodes-friday-night-pad-thai
Ivir, V. (1987). Procedures and strategies for the translation of culture. In G. Toury (Ed.), Translation across cultures (pp. 36–48). Bahri Publications.
Jiao, W., Wang, W., Huang, J.-T., Wang, X., & Tu, Z. (2023). Is ChatGPT a good translator? A preliminary study. arXiv. https://doi.org/10.48550/arXiv.2301.08745
Katan, D. (2004). Translating cultures: An introduction for translators, interpreters and mediators. St. Jerome.
Katan, D. (2009a). Culture. In M. Baker & G. Saldanha (Eds.), Routledge encyclopedia of translation studies (2nd ed., pp. 70–73). Routledge.
Katan, D. (2009b). Translation as intercultural communication. In J. Munday (Ed.), The Routledge companion to translation studies (pp. 74–92). Routledge.
Ketphromphon, S. (1999). Pha yan phra sihing [Phra Sihing incantation cloth]. In Saranukrom watthanatham thai phak nuea [Encyclopedia of northern Thai culture] (Vol. 8, pp. 4061–4069). Thai Culture Encyclopaedia Foundation, Siam Commercial Bank.
Koehn, P., & Knowles, R. (2017). Six challenges for neural machine translation. In T. Luong, A. Birch, G. Neubig, & A. Finch (Eds.), Proceedings of the first workshop on neural machine translation (pp. 28–39). Association for Computational Linguistics. https://doi.org/10.18653/v1/W17-3204
Kwieciński, P. (2001). Disturbing strangeness: Foreignisation and domestication in translation procedures in the context of cultural asymmetry. Wydawnictwo Edytor.
Łoboda, K., & Mastela, O. (2023). Machine translation and culture-bound texts in translator education: A pilot study. The Interpreter and Translator Trainer, 17(3), 503–525. https://doi.org/10.1080/1750399X.2023.2238328
Martikainen, H. (2019). Post-editing neural MT in medical LSP: Lexico-grammatical patterns and distortion in the communication of specialized knowledge. Informatics, 6(3), Article 26. https://doi.org/10.3390/informatics6030026
Masong, V., & Chakorn, O. (2023). Culture-bound elements in Thai literary translation: A case study of Marcel Barang’s Thai-English translation strategies. NIDA Case Research Journal, 15(2), 111–166. https://doi.org/10.14456/ncrj.2023.8
Merriam-Webster. (n.d.-a). Leprechaun. In Merriam-Webster.com dictionary. Retrieved May 22, 2024, from https://www.merriam-webster.com/dictionary/leprechaun
Merriam-Webster. (n.d.-b). Pad thai. In Merriam-Webster.com dictionary. Retrieved May 22, 2024, from https://www.merriam-webster.com/dictionary/pad%20thai
Microsoft. (n.d.). Languages. Retrieved October 6, 2024, from https://www.microsoft.com/en-us/translator/languages/
Microsoft Translator. (2018, April 18). Microsoft brings AI-powered translation to end users and developers, whether you’re online or offline. https://www.microsoft.com/en-us/translator/blog/2018/04/18/microsoft-brings-ai-powered-translation-to-end-users-and-developers-whether-youre-online-oroffline/
Montes Sánchez, A. (2025). From NMT to LLMs: A comparative study of translation technologies applied to Spanish restaurant menus. Perspectives, 34(4), 815–832. https://doi.org/10.1080/0907676X.2025.2600607
MSIG Thailand (2023, August 22). MSIG pen borisat prakan thi “chai” samrap khun rue yang? [Is MSIG the insurance “for” you?]. [Video]. YouTube. https://www.youtube.com/watch?v=3v68QzFYVCU
Newmark, P. (1988). A textbook of translation. Prentice Hall.
Ngern Tid Lor (2018, January 12). Prakan tid rot tong ngoen tit lo thoa nan!!! [Your car insurance should only be Ngern Tid Lor!!!] [Video]. YouTube. https://www.youtube.com/watch?v=mLRTxZQIbHY
Nimmanhemin, P. (1999a). Lek lai [Metal talisman]. In Saranukrom watthanatham thai phak klang [Encyclopedia of central Thai culture] (Vol. 15, p. 7217). Thai Culture Encyclopedia Foundation, Siam Commercial Bank.
Nimmanhemin, P. (1999b). Palat khik [Phallic amulet]. In Saranukrom watthanatham thai phak klang [Encyclopedia of central Thai culture] (Vol. 8, p. 3606). Thai Culture Encyclopedia Foundation, Siam Commercial Bank.
O’Donnell, L. (2024). Translation workflow and translated texts: Thai culture-specific items in community-based tourism brochures [Doctoral dissertation, Goldsmiths, University of London]. Goldsmiths Research Online. https://research.gold.ac.uk/id/eprint/36044/
Pedersen, J. (2017). The FAR model: Assessing quality in interlingual subtitling. The Journal of Specialised Translation, (28), 210–229. https://doi.org/10.26034/cm.jostrans.2017.239
Pinmanee, S. (2018). On the translation of culture-specific terms related to Thai superstitions and beliefs. Thoughts, 2018(1), 51–74. https://so06.tci-thaijo.org/index.php/thoughts/article/view/131670
Prakantidloh (2024, March 15). Khwam sabai chai [Peace of mind]. [Video]. YouTube. https://www.youtube.com/watch?v=9yLv-4XSu4g
Qiu, J., & Pym, A. (2025). Fatal flaws? Investigating the effects of machine translation errors on audience reception in the audiovisual context. Perspectives: Studies in Translatology, 33(5), 913–929.
https://doi.org/10.1080/0907676X.2024.2328757
Ragni, V., & Nunes Vieira, L. (2021). What has changed with neural machine translation? A critical review of human factors. Perspectives, 30(1), 137–158. https://doi.org/10.1080/0907676X.2021.1889005
Robinson, N. R., Ogayo, P., Mortensen, D. R., & Neubig, G. (2023). ChatGPT MT: Competitive for high-(but not low-) resource languages. arXiv. https://doi.org/10.48550/arXiv.2309.07423
Roekmongkhonwit, C. (2006). A study of translation strategies employed in Jatujak Market guidebook [Master’s thesis, Srinakharinwirot University]. SWU IR. http://thesis.swu.ac.th/swuthesis/Bus_Eng_Int_Com/Chaiyaporn_R.pdf
Roojai. (2024, January 1). Ru mai? Khotsana ni save hu khun dai [Do you know that this commercial can help protect your eardrums?] [Video]. YouTube. https://www.youtube.com/watch?v=R5iO0Vf6xhc
Schoening, S. (2023, November 13). The neural machine translation (r)evolution: Faster, higher, stronger. Phrase. https://phrase.com/blog/posts/neural-machine-translation-revolution/
Sennrich, R., Haddow, B., & Birch, A. (2016). Neural machine translation of rare words with subword units. In K. Erk & N. A. Smith (Eds.), Proceedings of the 54th annual meeting of the Association for Computational Linguistics (Vol. 1, pp. 1715–1725). Association for Computational Linguistics. https://doi.org/10.18653/v1/P16-1162
Silpa-Mag. (2022, January 10). Tamnan thepphrachao chin “machu” su “mae ya nang”: Phuenthi saksit chak huaruea thueng console rotyon [Chinese deities “Maju” to “Female guardian spirit”: Shifting the magical spaces from the prow to the car console]. Silapa Watthanatham. https://www.silpa-mag.com/history/article_59176
Tambiah, S. J. (1970). Buddhism and the spirit cults in North-East Thailand. Cambridge University Press.
The Royal Institute. (n.d.-a). Ruesi [Ascetic]. In Photchananukrom chabap ratchabandittayasathan phothoso 2554 [The Royal Institute Thai dictionary B.E. 2554]. Retrieved May 21, 2024, from https://dictionary.orst.go.th
The Royal Institute. (n.d.-b). Yan [Incantation]. In Photchananukrom chabap ratchabandittayasathan phothoso 2554 [The Royal Institute Thai dictionary B.E. 2554]. Retrieved May 21, 2024, from https://dictionary.orst.go.th
Tongpoon-Patanasorn, A., & Griffith, K. (2020). Google Translate and translation quality: A case of translating academic abstracts from Thai to English. PASAA, 60(1), 134–163. https://doi.org/10.58837/CHULA.PASAA.60.1.5
Toral, A., & Way, A. (2018). What level of quality can neural machine translation attain on literary text? In J. Moorkens, S. Castilho, F. Gaspari, & S. Doherty (Eds.), Translation quality assessment: From principles to practice (pp. 263–287). Springer. https://doi.org/10.1007/978-3-319-91241-7_12
Toral, A., Wieling, M., & Way, A. (2018). Post-editing effort of a novel with statistical and neural machine translation. Frontiers in Digital Humanities, 5, Article 9. https://doi.org/10.3389/fdigh.2018.00009
Vardaro, J., Schaeffer, M., & Hansen-Schirra, S. (2019). Translation quality and error recognition in professional neural machine translation post-editing. Informatics, 6(3), Article 41. https://doi.org/10.3390/informatics6030041
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds.), Advances in neural information processing systems (Vol. 30, pp. 5998–6008). Curran Associates. https://papers.nips.cc/paper/7181-attention-is-all-you-need
Venuti, L. (2008). The translator’s invisibility (2nd ed.). Routledge.
Walker, T. (2017, November 29). Introducing Amazon Translate: Real-time language translation. AWS. https://aws.amazon.com/blogs/aws/introducing-amazon-translate-real-time-text-language-translation/
Winnarong, K. (2025). On extralinguistic cultural reference: The translation of Thai color terms in English subtitles. rEFLections, 32(3), 1447–1469. https://doi.org/10.61508/refl.v32i3.284289
Wongseree, T. (2021). Translation of Thai culture-specific words into English in digital environment: Translators’ strategies and use of technology. rEFLections, 28(3), 334–356. https://doi.org/10.61508/refl.v28i3.254613
Wu, Y., Schuster, M., Chen, Z., Le, Q. V., & Norouzi, M. (2016). Google’s neural machine translation system: Bridging the gap between human and machine translation. arXiv. https://doi.org/10.48550/arXiv.1609.08144
Wyndham, A. (2021, September 15). Inside DeepL: The world’s fastest-growing, most secretive machine translation company. Slator. https://slator.com/inside-deepl-the-worlds-fastest-growing-most-secretive-machinetranslation-company/
Yamada, M. (2019). The impact of Google neural machine translation on post-editing by student translators. The Journal of Specialised Translation, (31), 87–106. https://doi.org/10.26034/cm.jostrans.2019.178
Zhivotova, A. A., Berdonosov, V. D., & Redkolis, E. V. (2020). Improving the quality of scientific articles machine translation while writing original text. In T. Devezas, J. Leitão, & A. Sarygulov (Eds.), 2020 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon) (pp. 1–4). IEEE. https://doi.org/10.1109/FarEastCon50210.2020.9271442
