<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-16T03:01:24Z</responseDate><request verb="GetRecord" identifier="oai:uvadoc.uva.es:10324/84393" metadataPrefix="marc">https://uvadoc.uva.es/oai/request</request><GetRecord><record><header><identifier>oai:uvadoc.uva.es:10324/84393</identifier><datestamp>2026-05-08T07:43:54Z</datestamp><setSpec>com_10324_1154</setSpec><setSpec>com_10324_931</setSpec><setSpec>com_10324_894</setSpec><setSpec>col_10324_1290</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dcterms="http://purl.org/dc/terms/" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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<subfield code="a">dc</subfield>
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<datafield tag="720" ind1=" " ind2=" ">
<subfield code="a">Sanz Valdivieso, Lucia</subfield>
<subfield code="e">author</subfield>
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<datafield tag="720" ind1=" " ind2=" ">
<subfield code="a">López Arroyo, María Belén</subfield>
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<datafield tag="260" ind1=" " ind2=" ">
<subfield code="c">2023</subfield>
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<subfield code="a">Experts and professionals in specialized fields often need writing tools&#xd;
to communicate in English as a means to disseminate their knowledge or enter&#xd;
the international market. There are different tools to accomplish this and most of&#xd;
them are, lately, Machine Translation systems (MT) based on Neural Machine&#xd;
Translation (NMT), an approach using artificial neural networks to translate with&#xd;
outstanding fluency. Free and open systems such as Google Translate or, more&#xd;
recently, ChatGPT used as a translator, have popularized NMT to a multitude of&#xd;
users. However, there are experts and professionals who, due to their lack of&#xd;
command of English, often fail in their communication tasks by accepting NMT&#xd;
system’s output as correct. This paper examines these systems’ performance&#xd;
when translating terminology of the discourse in wine and olive oil tasting notes,&#xd;
specifically from Spanish into English. This domain may serve to represent lessstudied&#xd;
specialized languages where general language words and terms become&#xd;
closely intertwined. The aim is to determine whether these systems can translate&#xd;
terminology accurately within the domain, and, if so, whether the GPT-3.5 model&#xd;
outperforms Google Translate. Results will help identify or discard possible language&#xd;
solutions for users who need to obtain texts in specialized English with&#xd;
professional and internationalization purposes, but who do not have the linguistic&#xd;
or economic resources to ensure the quality of the English text. Results show that,&#xd;
although ChatGPT yields fewer terminological errors than Google Translate in&#xd;
terms of error severity and number of samples affected, professionals cannot rely&#xd;
solely on these tools just yet.</subfield>
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<subfield code="a">Proceedings of the International Conference HiT-IT 2023</subfield>
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<subfield code="a">https://uvadoc.uva.es/handle/10324/84393</subfield>
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<datafield tag="024" ind2=" " ind1="8">
<subfield code="a">10.26615/issn.2683-0078.2023_008</subfield>
</datafield>
<datafield tag="024" ind2=" " ind1="8">
<subfield code="a">97</subfield>
</datafield>
<datafield tag="024" ind2=" " ind1="8">
<subfield code="a">107</subfield>
</datafield>
<datafield tag="245" ind1="0" ind2="0">
<subfield code="a">Google Translate vs. ChatGPT: Can non-language professionals trust them for specialized translation?</subfield>
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