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From FreEM to D'AlemBERT ; From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French
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In: Proceedings of the 13th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-03596653 ; Proceedings of the 13th Language Resources and Evaluation Conference, European Language Resources Association, Jun 2022, Marseille, France (2022)
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Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
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In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-03578503 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapour, Singapore (2022)
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Multistream neural architectures for cued-speech recognition using a pre-trained visual feature extractor and constrained CTC decoding
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In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-03578503 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, May 2022, Singapour, Singapore (2022)
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Genetic Neural Architecture Search for automatic assessment of human sperm images
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In: ISSN: 0957-4174 ; Expert Systems with Applications ; https://hal.archives-ouvertes.fr/hal-03585035 ; Expert Systems with Applications, Elsevier, 2022 (2022)
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Automatic Speech Recognition and Query By Example for Creole Languages Documentation
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In: Findings of the Association for Computational Linguistics: ACL 2022 ; https://hal.archives-ouvertes.fr/hal-03625303 ; Findings of the Association for Computational Linguistics: ACL 2022, May 2022, Dublin, Ireland (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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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (2022)
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Cross-Situational Learning Towards Robot Grounding
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In: https://hal.archives-ouvertes.fr/hal-03628290 ; 2022 (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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Estimating Vocal Tract Resonances of Synthesized High-Pitched Vowels Using CNN ...
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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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Chess AI: Competing Paradigms for Machine Intelligence
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In: Entropy; Volume 24; Issue 4; Pages: 550 (2022)
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Singing voice separation using waveform-level deep neural networks ... : Διαχωρισμός Φωνητικών χρησιμοποιώντας Βαθιά Νευρωνικά Δίκτυα σε Επίπεδο Κυματομορφών ...
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Καταστολή ηχητικού θορύβου μέσω τεχνικών μηχανικής μάθησης ...
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Can distributional semantics explain performance on the false belief task? ...
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