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Source or target first? Comparison of two post-editing strategies with translation students
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In: https://hal.archives-ouvertes.fr/hal-03546151 ; 2022 (2022)
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Automatic Normalisation of Early Modern French
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In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
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Offline Corpus Augmentation for English-Amharic Machine Translation
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In: 2022 The 5th International Conference on Information and Computer Technologies ; https://hal.archives-ouvertes.fr/hal-03547539 ; 2022 The 5th International Conference on Information and Computer Technologies, Mar 2022, New York, United States (2022)
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DeepL et Google Translate face à l'ambiguïté phraséologique
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In: https://hal.archives-ouvertes.fr/hal-03583995 ; 2022 (2022)
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From Disrupted Classrooms to Human-Machine Collaboration? The Pocket Calculator, Google Translate, and the Future of Language Education
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In: L2 Journal, vol 14, iss 1 (2022)
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Thirty Years of Machine Translation in Language Teaching and Learning: A Review of the Literature
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In: L2 Journal, vol 14, iss 1 (2022)
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A “Hands-On” Approach to Raise Awareness of Technologies: A Pilot Class and its Lessons
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In: L2 Journal, vol 14, iss 1 (2022)
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Do You Speak Translate?: Reflections on the Nature and Role of Translation
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In: L2 Journal, vol 14, iss 1 (2022)
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Exploring Foreign Language Students’ Perceptions of the Guided Use of Machine Translation (GUMT) Model for Korean Writing
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In: L2 Journal, vol 14, iss 1 (2022)
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Machine Translation: Friend or Foe in the Language Classroom?
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In: L2 Journal, vol 14, iss 1 (2022)
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Proficiency and the Use of Machine Translation: A Case Study of Four Japanese Learners
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In: L2 Journal, vol 14, iss 1 (2022)
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What’s Wrong with “What is your name?” > “Quel est votre nom?”:Teaching Responsible Use of MT through Discursive Competence and Metalanguage Awareness
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In: L2 Journal, vol 14, iss 1 (2022)
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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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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). 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 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 of 16 articles. Second, the NMT-generated translation of the metadata of 16 other articles was 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:
[SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SHS]Humanities and Social Sciences; Human metrics; human post-editing; machine translation (MT); machine translation evaluation; neural machine translation (NMT); publishing; translation quality
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URL: https://halshs.archives-ouvertes.fr/halshs-03603590
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The use of online translators by students not enrolled in a professional translation program: beyond copying and pasting for a professional use
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In: EAMT2022 (European Association for Machine Translation) ; https://hal.archives-ouvertes.fr/hal-03656029 ; EAMT2022 (European Association for Machine Translation), Jun 2022, Ghent, Belgium ; https://eamt2022.com/ (2022)
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Le modèle Transformer: un « couteau suisse » pour le traitement automatique des langues
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In: Techniques de l'Ingenieur ; https://hal.archives-ouvertes.fr/hal-03619077 ; Techniques de l'Ingenieur, Techniques de l'ingénieur, 2022, ⟨10.51257/a-v1-in195⟩ ; https://www.techniques-ingenieur.fr/base-documentaire/innovation-th10/innovations-en-electronique-et-tic-42257210/transformer-des-reseaux-de-neurones-pour-le-traitement-automatique-des-langues-in195/ (2022)
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The use of MT by undergraduate translation students for different learning tasks
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In: https://hal.archives-ouvertes.fr/hal-03547415 ; 2022 (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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АКТУАЛЬНЫЕ ТЕНДЕНЦИИ ЦИФРОВИЗАЦИИ ИНОЯЗЫЧНОГО ОБУЧЕНИЯ В НЕЯЗЫКОВОМ ВУЗЕ ... : CURRENT TRENDS IN DIGITALIZATION OF FOREIGN LANGUAGE EDUCATION IN A NON-LINGUISTIC UNIVERSITY ...
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Maschinelle Übersetzung (MT) für den Notfall : Ratgeber zum Einsatz von MT Tools für die Kommunikation mit Flüchtlingen aus der Ukraine ...
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Neural machine translation and language teaching : possible implications for the CEFR ...
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