2026-05-16T01:46:10Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/843932026-05-08T07:43:54Zcom_10324_1154com_10324_931com_10324_894col_10324_1290

Sanz Valdivieso, Lucia f2390245407dc9e5 600 0000-0001-5772-8041 López Arroyo, María Belén 20c61cb4d75948ca 600 0000-0002-9171-1910 2026-05-05T20:23:20Z 2026-05-05T20:23:20Z 2023 Proceedings of the International Conference HiT-IT 2023 https://uvadoc.uva.es/handle/10324/84393 10.26615/issn.2683-0078.2023_008 97 107 Experts and professionals in specialized fields often need writing tools to communicate in English as a means to disseminate their knowledge or enter the international market. There are different tools to accomplish this and most of them are, lately, Machine Translation systems (MT) based on Neural Machine Translation (NMT), an approach using artificial neural networks to translate with outstanding fluency. Free and open systems such as Google Translate or, more recently, ChatGPT used as a translator, have popularized NMT to a multitude of users. However, there are experts and professionals who, due to their lack of command of English, often fail in their communication tasks by accepting NMT system’s output as correct. This paper examines these systems’ performance when translating terminology of the discourse in wine and olive oil tasting notes, specifically from Spanish into English. This domain may serve to represent lessstudied specialized languages where general language words and terms become closely intertwined. The aim is to determine whether these systems can translate terminology accurately within the domain, and, if so, whether the GPT-3.5 model outperforms Google Translate. Results will help identify or discard possible language solutions for users who need to obtain texts in specialized English with professional and internationalization purposes, but who do not have the linguistic or economic resources to ensure the quality of the English text. Results show that, although ChatGPT yields fewer terminological errors than Google Translate in terms of error severity and number of samples affected, professionals cannot rely solely on these tools just yet. Lenguajes naturales controlados, comunicación colaborativa y producción textual bilingüe en entornos 3.0 (PID2020-114064RB-I00), supported financially by the Ministerio de Educación y Ciencia de España, and the project Writing Audit: Evaluación de la redacción técnica con entornos visuals (PID-078) supported financially by the University of Valladolid. Lucía Sanz-Valdivieso develops her research under a fellowship granted by the Ministerio de Educación (FPU20-00293). application/pdf eng Hit IT info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0/ Attribution-NonCommercial-NoDerivatives 4.0 Internacional Google Translate vs. ChatGPT: Can non-language professionals trust them for specialized translation? info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion SI 5701.12 Traducción THUMBNAIL Naples_2023_ChatGPT vs. GoogleTranslate_HiT-IT-2023-proceedings.pdf.jpg Naples_2023_ChatGPT vs. GoogleTranslate_HiT-IT-2023-proceedings.pdf.jpg IM Thumbnail image/jpeg 4098 https://uvadoc.uva.es/bitstream/10324/84393/3/Naples_2023_ChatGPT%20vs.%20GoogleTranslate_HiT-IT-2023-proceedings.pdf.jpg 0c94c0b843843ab54ef4ee184705bb95 MD5 3 LICENSE license.txt license.txt text/plain 3929 https://uvadoc.uva.es/bitstream/10324/84393/2/license.txt 289d98c1665ee0d20312360f0e8643c8 MD5 2 ORIGINAL Naples_2023_ChatGPT vs. GoogleTranslate_HiT-IT-2023-proceedings.pdf Naples_2023_ChatGPT vs. GoogleTranslate_HiT-IT-2023-proceedings.pdf application/pdf 398700 https://uvadoc.uva.es/bitstream/10324/84393/1/Naples_2023_ChatGPT%20vs.%20GoogleTranslate_HiT-IT-2023-proceedings.pdf 5e75d241218a27193a7bdcae0aeb8ba3 MD5 1 10324/84393 oai:uvadoc.uva.es:10324/84393 2026-05-08 09:43:54.283 UVaDOC repositorio@uva.es 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