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1	Automatic Normalisation of Early Modern French
	Bawden, Rachel; Poinhos, Jonathan; Kogkitsidou, Eleni...
	In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
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2	National Languages, Multilingual Education, and the Self-proclaimed "Militants" for Change in Senegal
	Iwasaki, Erina. - 2022
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3	From FreEM to D'AlemBERT ; From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French
	Gabay, Simon; Ortiz Suarez, Pedro; Bartz, Alexandre; Chagué, Alix; Bawden, Rachel; Gambette, Philippe; Sagot, Benoît
	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)
	Abstract: 8 pages, 2 figures, 4 tables ; International audience ; Language models for historical states of language are becoming increasingly important to allow the optimal digitisation and analysis of old textual sources. Because these historical states are at the same time more complex to process and more scarce in the corpora available, specific efforts are necessary to train natural language processing (NLP) tools adapted to the data. In this paper, we present our efforts to develop NLP tools for Early Modern French (historical French from the 16th to the 18th centuries). We present the FreEMmax corpus of Early Modern French and D'AlemBERT, a RoBERTa-based language model trained on FreEMmax. We evaluate the usefulness of D'AlemBERT by fine-tuning it on a part-of-speech tagging task, outperforming previous work on the test set. Importantly, we find evidence for the transfer learning capacity of the language model, since its performance on lesser-resourced time periods appears to have been boosted by the more resourced ones. We release D'AlemBERT and the open-sourced subpart of the FreEMmax corpus.
	Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Corpus creation; Création de corpus; Digital humanities; Early Modern French; Français classique; Humanités Numériques; Language modelling; Langues peu dotées; Less-resourced languages; Modèle de langue neuronal; Modélisation linguistique; Neural language representation models; Partie du discours; POS tagging
	URL: https://hal.inria.fr/hal-03596653
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4	From Tamajaght to French. To translate is to betray, but how far? ; De la tamajaght au français. Traduire, c’est trahir, mais jusqu’où ?
	Claudot-Hawad, Hélène
	In: IFS. Tasɣunt n wannas d tɣerma tamaziɣt / Revue de culture et de civilisation amazighe ; https://halshs.archives-ouvertes.fr/halshs-03650005 ; IFS. Tasɣunt n wannas d tɣerma tamaziɣt / Revue de culture et de civilisation amazighe, Criniere du lion, A paraître, pp.7-28 (2022)
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5	Against 'failing francophony', a reflection on francophonies ; Contre la « francophonie défaillante », penser les francophonies
	Lorilleux, Joanna
	In: Apprentissages et politiques éducatives. Quelles interdisciplinarités, méthodologies et perspectives internationales ? ; https://hal-univ-tours.archives-ouvertes.fr/hal-03618378 ; M. Gadille. Apprentissages et politiques éducatives. Quelles interdisciplinarités, méthodologies et perspectives internationales ?, Sciendo, In press, Apprentissages et politiques éducatives. Quelles interdisciplinarités, méthodologies et perspectives internationales ? (2022)
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6	Adopter une approche diachronique et contextualisante pour explorer le rapport à l’écrit : l’intérêt d’une prise en compte des répertoires langagiers et des environnements de socialisation.
	Delebarre, Justine
	In: ISSN: 2706-6312 ; EISSN: 2708-0633 ; Akofena - Revue scientifique des Sciences du Langage, Lettres, Langues & Communication, ; https://hal.archives-ouvertes.fr/hal-03551355 ; Akofena - Revue scientifique des Sciences du Langage, Lettres, Langues & Communication, , L3DL-CI, Université Félix Houphouët-Boigny, 2022 (2022)
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7	How children and adults describe events and their causes ...
	Salfner, Fabienne. - : Open Science Framework, 2022
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8	CFPR: interview avec FRA2020_0106
	In: https://nakala.fr/10.34847/nkl.9718w42c#9e8b7ad6d66189180cae526b9b9c4459bef45358 (2022)
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9	CFPR: interview avec FRA2019_0126
	In: https://nakala.fr/10.34847/nkl.cbca87ye#0584e13bf6cccc297040b2b67dc199829fff3f86 (2022)
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10	CFPR: interview avec SUI2019_0106
	In: https://nakala.fr/10.34847/nkl.7c1ff45v#e31d35c535f757cc5605c81eeb89c32d23c44607 (2022)
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11	CFPR: interview avec CAN2019_0037
	In: https://nakala.fr/10.34847/nkl.004c8p5q#9464bfe9a3ad89dfd5e2d1a4288e057cb730aae6 (2022)
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12	CFPR: interview avec MAU2019_0010
	In: https://nakala.fr/10.34847/nkl.e16ci8ai#7de629ef7666ccd2124574d0212ecc46199268ba (2022)
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13	CFPR: interview avec FRA2019_0048
	In: https://nakala.fr/10.34847/nkl.b07axypw#0cef90f9b13077c82d633bd93ffae4c3d002f461 (2022)
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14	CFPR: interview avec FRA2019_0013
	In: https://nakala.fr/10.34847/nkl.44f01w50#2a6c61fcfd7ea942f2b99ae9bfd744469db12ada (2022)
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15	CFPR: interview avec FRA2020_0038
	In: https://nakala.fr/10.34847/nkl.59d6s6z2#967267acb95f6da8641a7aa1d7e766e4ddf9c309 (2022)
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16	CFPR: interview avec FRA2021_0018
	In: https://nakala.fr/10.34847/nkl.af8a463l#7114c0ac1155351dad8715762ec6807522e8a6d7 (2022)
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17	CFPR: interview avec FRA2020_0109
	In: https://nakala.fr/10.34847/nkl.ec4diq5a#906e58364f698b68d3cfc85ccc2b30ae4ff3b24c (2022)
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18	CFPR: interview avec FRA2019_0047
	In: https://nakala.fr/10.34847/nkl.56a722j8#403d00116a23719c42d6521430e112eb6b03eb2d (2022)
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19	CFPR: interview avec FRA2019_0031
	In: https://nakala.fr/10.34847/nkl.7d2b5lj5#d41918678d8c8d82b89edf6bb681b1f26e0a37d7 (2022)
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20	CFPR: interview avec FRA2019_0129
	In: https://nakala.fr/10.34847/nkl.bafec330#fd73b34562dff1520b5f691dfee3d06927660f41 (2022)
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