Towards AI-supported Health Communication in Plain Language: Evaluating Intralingual Machine Translation of Medical Texts

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A5JK29LZF" target="_blank" >RIV/00216208:11320/25:5JK29LZF - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195213804&partnerID=40&md5=0c7f3da21b2d0d4999d0981655a042b8" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195213804&partnerID=40&md5=0c7f3da21b2d0d4999d0981655a042b8</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Towards AI-supported Health Communication in Plain Language: Evaluating Intralingual Machine Translation of Medical Texts

Popis výsledku v původním jazyce

In this paper, we describe results of a study on evaluation of intralingual machine translation. The study focuses on machine translations of medical texts into Plain German. The automatically simplified texts were compared with manually simplified texts (i.e., simplified by human experts) as well as with the underlying, unsimplified source texts. We analyse the quality of the translations based on different criteria, such as correctness, readability, and syntactic complexity. The study revealed that the machine translations were easier to read than the source texts, but contained a higher number of complex syntactic relations than the human translations. Furthermore, we identified various types of mistakes. These included not only grammatical mistakes but also content-related mistakes that resulted, for example, from mistranslations of grammatical structures, ambiguous words or numbers, omissions of relevant prefixes or negation, and incorrect explanations of technical terms. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Název v anglickém jazyce

Towards AI-supported Health Communication in Plain Language: Evaluating Intralingual Machine Translation of Medical Texts

Popis výsledku anglicky

In this paper, we describe results of a study on evaluation of intralingual machine translation. The study focuses on machine translations of medical texts into Plain German. The automatically simplified texts were compared with manually simplified texts (i.e., simplified by human experts) as well as with the underlying, unsimplified source texts. We analyse the quality of the translations based on different criteria, such as correctness, readability, and syntactic complexity. The study revealed that the machine translations were easier to read than the source texts, but contained a higher number of complex syntactic relations than the human translations. Furthermore, we identified various types of mistakes. These included not only grammatical mistakes but also content-related mistakes that resulted, for example, from mistranslations of grammatical structures, ambiguous words or numbers, omissions of relevant prefixes or negation, and incorrect explanations of technical terms. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Workshop Patient-Oriented Lang. Process., CL4Health LREC-COLING - Workshop Proc.

ISBN

978-249381425-8

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

44-53

Název nakladatele

European Language Resources Association (ELRA)

Místo vydání

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Místo konání akce

Torino, Italia

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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