Human and machine translation: a comparative analysis of neural machine- and human-translated EN-HU and HU-EN legal texts

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dc.contributor.authorKovács Tímea
dc.contributor.departmentAnglisztika Intézet
dc.contributor.departmentAngol Nyelvi Tanszék
dc.contributor.editorBesznyák Rita (szerkesztő)
dc.contributor.editorBocz Zsuzsanna (főszerkesztő)
dc.contributor.institutionKRE - Bölcsészet- és Társadalomtudományi Kar
dc.date.accessioned2024-06-06T10:44:43Z
dc.date.available2024-06-06T10:44:43Z
dc.date.issued2022
dc.description.abstractAs neural machine translation is increasingly more capable of modelling how natural languages work, the traditional tasks of translators are being gradually replaced by new challenges (Castilho et al., 2019). Consequently, more emphasis is placed on pre- and post-editing (revision) skills and competences (Pym, 2013; Robert et al., 2017), enabling the production of higher quality and near human-made translations. Therefore, the efficiency of pre- and postediting largely depends on how aware translators are of the mechanisms and limitations of neural machine translation tools adopted in given language pairs (Lample et al., 2018). This paper aims to demonstrate through the comparison of the neural machine and human-translated English and Hungarian translations of Hungary’s Fundamental Law and the U.S. Constitution, respectively, the different challenges arising in the course of translation and posed by posteditors, especially from the perspective of comprehensibility and well-formedness.
dc.format.page9 p
dc.identifier.citationKovács Tímea: Human and machine translation: a comparative analysis of neural machine- and human-translated EN-HU and HU-EN legal texts. Porta Lingua 2022/1. 49-57 p.
dc.identifier.doi https://doi.org/10.48040/PL.2022.1.5
dc.identifier.issn2064-3381 (online)
dc.identifier.mtmt32916638
dc.identifier.uri https://krepozit.kre.hu/handle/123456789/1213
dc.languageAngol
dc.language.isoen
dc.relation.ispartofPorta Lingua
dc.subject.classificationangol nyelvészet
dc.titleHuman and machine translation: a comparative analysis of neural machine- and human-translated EN-HU and HU-EN legal texts
dc.typeArticle
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