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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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Abstract:
International audience ; The purpose of this study was to investigate the effect of corpus augmentation on the quality of English-Amharic Machine Translation (MT). In fact, trigram and four-gram Statistical Machine Translation (SMT) language models, as well as Neural Machine Translation (NMT) models based on Gated Recurrent Units (GRU) were used. They were trained independently using both the original and augmented corpus to see how the augmentation of the corpus affects the translation quality of these models. These two corpora (original and augmented) contain 225,304 and 463,796 English-Amharic parallel sentences respectively. To complete the corpus augmentation challenge, an offline token level tokenization technique was used. This technique (corpus augmentation) was used before any other MT processes were started. Among several token-level tokenization mechanisms, random insertion, replacement, deletion, and swapping approaches were chosen and implemented. After both models had been trained, the Bilingual Evaluation Understudy (BLEU) ratings were collected and analyzed. Our results demonstrate that the models trained with the augmented corpus outperform their corresponding models (models trained with the original corpus) in terms of BLEU scores. As a result, we can conclude that corpus augmentation did indeed help in the improvement of the performance of both SMT and NMT translation systems.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Amharic language; Corpus Augmentation; GRU; Machine Translation; NMT; SMT; Token level augmentation
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URL: https://hal.archives-ouvertes.fr/hal-03547539 https://hal.archives-ouvertes.fr/hal-03547539/file/ICICT2022Augmented_corpusFinal%20Draft.pdf https://hal.archives-ouvertes.fr/hal-03547539/document
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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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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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