TRANSLATING LAW: A COMPARISON OF HUMAN AND POST-EDITED TRANSLATIONS FROM GREEK TO ENGLISH

Advances in neural machine translation (NMT) models have led to reported improvements in machine translation (MT) outputs, especially for resource-rich language pairs (Deng & Liu, 2018), mainly at the level of fluency (Castilho et al., 2017a, 2017b). NMT systems have been used particularly for t...

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Published in:Revista de llengua i dret no. 78; p. 92
Main Authors: Sosoni, Vilelmini, O'Shea, John, Stasimioti, Maria
Format: Journal Article
Language:English
Published: Barcelona Escola d'Administracio Publica de Catalunya 01-12-2022
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Abstract Advances in neural machine translation (NMT) models have led to reported improvements in machine translation (MT) outputs, especially for resource-rich language pairs (Deng & Liu, 2018), mainly at the level of fluency (Castilho et al., 2017a, 2017b). NMT systems have been used particularly for the translation of technical and life science texts with short, repetitive, formulaic, and unambiguous sentence types. In contrast, legal translation studies scholars have depicted legal translation as not particularly compatible with MT, mainly because legal texts include features that pose significant challenges to MT (Killman, 2014; Prieto Ramos, 2015; Matthiesen, 2017). As such, the quality of the output varies according to the legal genre and language pair. Using MQM-DQF error typology, this study evaluates the quality of the post-edited and human translation (HT) products of two normative property law texts from Greek to English, a language pair considered to be under-resourced. The time taken by the two translators who participated in the study to complete these products was monitored, and information was collected on their attitudes towards MT and post-editing (PE). The findings indicate neither productivity gains in the case of PE, nor major differences in accuracy or fluency between the post-edited and HT texts, although the number of errors was slightly higher overall in the case of HT, with most occurring at the level of accuracy. Conversely, the post-edited versions contained more errors at the levels of style and verity. Finally, the translators' views on MT and PE were dependent on the MT output quality, while their trust level in the output may have affected the end-product quality.
AbstractList Advances in neural machine translation (NMT) models have led to reported improvements in machine translation (MT) outputs, especially for resource-rich language pairs (Deng & Liu, 2018), mainly at the level of fluency (Castilho et al., 2017a, 2017b). NMT systems have been used particularly for the translation of technical and life science texts with short, repetitive, formulaic, and unambiguous sentence types. In contrast, legal translation studies scholars have depicted legal translation as not particularly compatible with MT, mainly because legal texts include features that pose significant challenges to MT (Killman, 2014; Prieto Ramos, 2015; Matthiesen, 2017). As such, the quality of the output varies according to the legal genre and language pair. Using MQM-DQF error typology, this study evaluates the quality of the post-edited and human translation (HT) products of two normative property law texts from Greek to English, a language pair considered to be under-resourced. The time taken by the two translators who participated in the study to complete these products was monitored, and information was collected on their attitudes towards MT and post-editing (PE). The findings indicate neither productivity gains in the case of PE, nor major differences in accuracy or fluency between the post-edited and HT texts, although the number of errors was slightly higher overall in the case of HT, with most occurring at the level of accuracy. Conversely, the post-edited versions contained more errors at the levels of style and verity. Finally, the translators' views on MT and PE were dependent on the MT output quality, while their trust level in the output may have affected the end-product quality.
Author Sosoni, Vilelmini
O'Shea, John
Stasimioti, Maria
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SubjectTerms English language
Fluency
Greek language
Language typology
Legal language
Machine translation
Translations
Translators
Title TRANSLATING LAW: A COMPARISON OF HUMAN AND POST-EDITED TRANSLATIONS FROM GREEK TO ENGLISH
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