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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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Abstract:
International audience ; The study of old state of languages is facing a double problem : on the one hand the distance with contemporary spelling prevents scholars from using standard NLP solutions, on the other hand the instability of the scriptae complexifies the training of solutions directly on the original source text. Returning to this problem with a DH perspective, we start with the philological reasoning behind the creation of the training corpus, and use traditional NLP methods to compare two machine translation systems (statistical and neural) and offer a functional tool for the normalisation of 17th c. French answering the needs of philologists. Mots-clés : Normalisation, XVII e siècle, traduction automatique neuronale, traduction automa-tique statistique, humanités numériques. ; L'étude des états de langue anciens se heurte à un double problème : d'une part la distance d'avec l'orthographe actuelle, qui empêche de recourir aux solutions standards de TAL, et d'autre part l'in-stabilité des systèmes graphiques, qui complexifie l'entraînement de solutions directement sur le texte original. Reprenant ce problème d'un point de vue des humanités numériques, nous partons du raisonnement philologique qui sous-tend la création du corpus d'entraînement, avant de recourir aux méthodes traditionnelles de TAL pour comparer deux systèmes de traduction automatique (sta-tistique et neuronale) et offrir un outil fonctionnel pour la normalisation du français classique qui corresponde aux besoins des philologues.
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Keyword:
17th c French; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SHS.LITT]Humanities and Social Sciences/Literature; Digital humanities; Français classique; Humanités numériques; Neural Machine Translation (NMT); Normalisation; Statistical Machine Translation (SMT); Traduction automatique neuronale; Traduction automatique statistique
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URL: https://hal.archives-ouvertes.fr/hal-02596669/file/main.pdf
https://hal.archives-ouvertes.fr/hal-02596669
https://hal.archives-ouvertes.fr/hal-02596669/document
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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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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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