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Neural MT and Human Post-editing : a Method to Improve Editorial Quality
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In: ISSN: 1134-8941 ; Interlingüística ; https://halshs.archives-ouvertes.fr/halshs-03603590 ; Interlingüística, Alacant [Spain] : Universitat Autònoma de Barcelona, 2022, pp.15-36 (2022)
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Machine Translation and Gender biases in video game localisation: a corpus-based analysis
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In: https://hal.archives-ouvertes.fr/hal-03540605 ; 2022 (2022)
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Multi-domain Neural Machine Translation ; Traduction automatique neuronale multidomaine
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In: https://tel.archives-ouvertes.fr/tel-03546910 ; Artificial Intelligence [cs.AI]. Université Paris-Saclay, 2021. English. ⟨NNT : 2021UPASG109⟩ (2021)
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A Transformer-Based Neural Machine Translation Model for Arabic Dialects That Utilizes Subword Units
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In: Sensors ; Volume 21 ; Issue 19 (2021)
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A Reception Study of Machine-Translated Easy Language Text by Individuals with Reading Difficulties
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In: 3rd International Conference on Translation, Interpreting and Cognition (ICTIC3) (2021) (2021)
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Cadlaws - An Enlgish-French parallel corpus of legally equivalent documents
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Cadlaws – An English–French Parallel Corpus of Legally Equivalent Documents
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In: Mutatis Mutandis: Revista Latinoamericana de Traducción, ISSN 2011-799X, Vol. 14, Nº. 2, 2021 (Ejemplar dedicado a: Nuevas perspectivas de investigación en la traducción especializada en lenguas románicas: aspectos comparativos, léxicos, fraseológicos, discursivos y didácticos), pags. 494-508 (2021)
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Machine Translation for the Normalisation of 17th c. French ; Traduction automatique pour la normalisation du français du XVII e siècle
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In: TALN 2020 ; https://hal.archives-ouvertes.fr/hal-02596669 ; TALN 2020, ATALA, Jun 2020, Nancy, France (2020)
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Bridging the “gApp”: improving neural machine translation systems for multiword expression detection
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In: 11 ; 1 ; 61 ; 80 (2020)
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| 11 |
Neural MT and Human Post-editing: a Method to Improve Editorial Quality
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In: Symposium Translation and Knowledge Transfer: News trends in the theory and practice of translation and interpreting ; https://hal.univ-rennes2.fr/hal-02495919 ; Symposium Translation and Knowledge Transfer: News trends in the theory and practice of translation and interpreting, Mar Ogea-Pozo, Carmen Expósito-Castro, Oct 2019, Cordoue, Spain (2019)
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Abstract:
International audience ; Machine translation (MT) has put more and more pressure on translators, especially since neural MT outperforms statistical MT. NMT provides better quality translations (more accurate and natural), and becomes closer to human translation. Yet, human translators must demonstrate their expertise and added value over such systems.Our study is based on an on-going project in partnership with Presses Universitaires de Rennes (PUR, one of the major French publishers), Maison des Sciences de l’Homme en Bretagne (French Centre for Human Sciences) and the TRASILT team (Translation, Linguistic Engineering and Terminology) within LIDILE research unit (Language Linguistics and Teaching, EA 3874). It consists in devising a method for researchers that combines NMT (DeepL) and human post-editing to improve the quality of article metadata (abstracts, keywords, contents, etc.) from French to English in the editorial process of journals. The objective is to develop a methodology for translation that can be reproduced and transferred to other journals and disciplinary fields. Based on the metadata of 75 articles published in 2017 in 4 PUR journals, it was decided to first compare the previously published English translation of these metadata with the NMT-generated translation of the same data. Second, an enriched version of the metadata (combining best translations from both outputs) will be post-edited and further improved by professional translators. Our goal is to determine the qualitative elements and limitations of each output (human vs. NMT) and design the most appropriate translation method. The method will then be tested on the 2020 issues of the 4 selected journals.
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Keyword:
[SCCO.LING]Cognitive science/Linguistics; [SHS.INFO]Humanities and Social Sciences/Library and information sciences; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; Human post-editing; machine translation (MT); neural machine translation (NMT); publishing; translation quality
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URL: https://hal.univ-rennes2.fr/hal-02495919
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Measuring the Impact of Neural Machine Translation on Easy-to-Read Texts: An Exploratory Study
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In: Conference on Easy-to-Read Language Research (Klaara 2019) (2019) (2019)
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Preferences of end-users for raw and post-edited NMT in a business environment
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In: ISBN: 978-2970-10957-0 ; Proceedings of the 41st Conference Translating and the Computer pp. 47-59 (2019)
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