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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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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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Neural machine translation and language teaching : possible implications for the CEFR ...
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MCSQ Translation Models (en-ru) (v1.0)
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Variš, Dušan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2022
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MCSQ Translation Models (en-de) (v1.0)
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Variš, Dušan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2022
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Characterizing News Portrayal of Civil Unrest in Hong Kong, 1998–2020 ...
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An Initial Investigation of Neural Decompilation for WebAssembly ; En Första Undersökning av Neural Dekompilering för WebAssembly
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Benali, Adam. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2022
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Lexical Diversity in Statistical and Neural Machine Translation
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In: Information; Volume 13; Issue 2; Pages: 93 (2022)
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A Survey of Automatic Source Code Summarization
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In: Symmetry; Volume 14; Issue 3; Pages: 471 (2022)
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Neural Models for Measuring Confidence on Interactive Machine Translation Systems
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1100 (2022)
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Impact of Sentence Representation Matching in Neural Machine Translation
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1313 (2022)
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Retrieval-Based Transformer Pseudocode Generation
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In: Mathematics; Volume 10; Issue 4; Pages: 604 (2022)
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Evaluating the Impact of Integrating Similar Translations into Neural Machine Translation
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In: Information; Volume 13; Issue 1; Pages: 19 (2022)
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Abstract:
Previous research has shown that simple methods of augmenting machine translation training data and input sentences with translations of similar sentences (or fuzzy matches), retrieved from a translation memory or bilingual corpus, lead to considerable improvements in translation quality, as assessed by a limited set of automatic evaluation metrics. In this study, we extend this evaluation by calculating a wider range of automated quality metrics that tap into different aspects of translation quality and by performing manual MT error analysis. Moreover, we investigate in more detail how fuzzy matches influence translations and where potential quality improvements could still be made by carrying out a series of quantitative analyses that focus on different characteristics of the retrieved fuzzy matches. The automated evaluation shows that the quality of NFR translations is higher than the NMT baseline in terms of all metrics. However, the manual error analysis did not reveal a difference between the two systems in terms of total number of translation errors; yet, different profiles emerged when considering the types of errors made. Finally, in our analysis of how fuzzy matches influence NFR translations, we identified a number of features that could be used to improve the selection of fuzzy matches for NFR data augmentation.
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Keyword:
evaluation; neural machine translation; translation memory
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URL: https://doi.org/10.3390/info13010019
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Some Contributions to Interactive Machine Translation and to the Applications of Machine Translation for Historical Documents
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Neural-based Knowledge Transfer in Natural Language Processing
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Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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Gender Bias in Neural Translation: a preliminary study ; Biais de genre dans un système de traduction automatique neuronale : une étude préliminaire
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In: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03265895 ; Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.11-25 ; https://talnrecital2021.inria.fr/ (2021)
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