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1
Source or target first? Comparison of two post-editing strategies with translation students
In: https://hal.archives-ouvertes.fr/hal-03546151 ; 2022 (2022)
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2
Automatic Normalisation of Early Modern French
In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
Abstract: Spelling normalisation is a useful step in the study and analysis of historical language texts, whether it is manual analysis by experts or automatic analysis using downstream natural language processing (NLP) tools. Not only does it help to homogenise the variable spelling that often exists in historical texts, but it also facilitates the use of off-the-shelf contemporary NLP tools, if contemporary spelling conventions are used for normalisation. We present FreEMnorm, a new benchmark for the normalisation of Early Modern French (from the 17th century) into contemporary French and provide a thorough comparison of three different normalisation methods: ABA, an alignment-based approach and MT-approaches, (both statistical and neural), including extensive parameter searching, which is often missing in the normalisation literature.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Digital Humanities; Historical; Machine Translation; Modern French; Normalisation; Spelling
URL: https://hal.inria.fr/hal-03540226/document
https://doi.org/10.5281/zenodo.5865428
https://hal.inria.fr/hal-03540226
https://hal.inria.fr/hal-03540226/file/LREC_2022_ModFr_Normalisation-18.pdf
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3
DeepL et Google Translate face à l'ambiguïté phraséologique
In: https://hal.archives-ouvertes.fr/hal-03583995 ; 2022 (2022)
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4
The use of MT by undergraduate translation students for different learning tasks
In: https://hal.archives-ouvertes.fr/hal-03547415 ; 2022 (2022)
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5
Machine Translation and Gender biases in video game localisation: a corpus-based analysis
In: https://hal.archives-ouvertes.fr/hal-03540605 ; 2022 (2022)
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6
АКТУАЛЬНЫЕ ТЕНДЕНЦИИ ЦИФРОВИЗАЦИИ ИНОЯЗЫЧНОГО ОБУЧЕНИЯ В НЕЯЗЫКОВОМ ВУЗЕ ... : CURRENT TRENDS IN DIGITALIZATION OF FOREIGN LANGUAGE EDUCATION IN A NON-LINGUISTIC UNIVERSITY ...
Е.Б. Манахова. - : Мир науки, культуры, образования, 2022
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7
Machine-readable Finnish-Livvi bilingual translation dictionary ...
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8
Machine-readable Finnish-Karelian bilingual translation dictionary ...
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9
Machine-readable Finnish-Karelian bilingual translation dictionary ...
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10
Machine-readable Northern Karelian Proper-Livvi bilingual translation dictionary ...
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11
Machine-readable Finnish-Livvi bilingual translation dictionary ...
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12
Machine-readable Northern Karelian Proper-Livvi bilingual translation dictionary ...
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13
MCSQ Translation Models (en-ru) (v1.0)
Variš, Dušan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2022
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14
MCSQ Translation Models (en-de) (v1.0)
Variš, Dušan. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2022
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15
DESIGNING TO SUPPORT SENSEMAKING IN CROSS-LINGUAL COMPUTER-MEDIATED COMMUNICATION USING NLP TECHNIQUES
Lim, Hajin. - 2021
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16
CENTRAL KURDISH MACHINE TRANSLATION: FIRST LARGE SCALE PARALLEL CORPUS AND EXPERIMENTS
In: https://hal.archives-ouvertes.fr/hal-03263105 ; 2021 (2021)
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17
Kittajafr-v2baseline-2.0.1
In: https://hal.archives-ouvertes.fr/hal-03503325 ; 2021 (2021)
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18
Kittajafr-v1-1.0.0
In: https://hal.archives-ouvertes.fr/hal-03172321 ; 2021 (2021)
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19
The EUTRANS-I corpus ...
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20
ENGLISH-AKUAPEM TWI PARALLEL CORPUS ...
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