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Why, What and How to help each Citizen to Understand Artificial Intelligence?
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In: EISSN: 0933-1875 ; KI - Künstliche Intelligenz ; https://hal.inria.fr/hal-03024034 ; KI - Künstliche Intelligenz, Springer Nature, 2021, pp.1610-1987 (2021)
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Rapport d'Activités Inria Learning Lab 2018
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In: https://hal.inria.fr/hal-02887836 ; [Autre] Inria. 2019 (2019)
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ERP evidence of fast learning of a second language vocabulary: New labels and existing concepts
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In: EUROSLA 25 ; https://hal.archives-ouvertes.fr/hal-01498825 ; EUROSLA 25, Aug 2015, Aix-en-Provence, France (2015)
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Abstract:
What does it take to acquire a semantic network in a second language? The present ERP study shows extremely rapid instantiation of both learned words and related concepts, via computerized games. Participants served as their own control. Electrical activity of the brain, recorded at the scalp, was examined prior to exposure with the second language and 8 days later, following a 6 day training session (preceded and followed by orientation and consolidation, respectively). Participants learned 12 words per day (nouns and verbs), for a total of 72 words over 6 consecutive days. Results show rapid changes in cortical activity, associated with learning. Prior to exposure, no modulation of the N400 component was found as a function of the correct match vs. mismatch of audio presentation of words and their associated images. Post training, a large N400 effect was found for mismatch trials compared to correctly matched audio-visual trials. More importantly, images that were semantically related to learned words (eg. for the learned word “horse” the image of a saddle was presented), produced a reduction of the N400 compared to mismatched pairs (eg. the image of a building followed by the auditory presentation of the same learned word “horse”). Our results attest to the plasticity of adult learners' brains and provide evidence for rapid onset of a semantic network in a late learned language.
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Keyword:
[SCCO.LING]Cognitive science/Linguistics; [SCCO.PSYC]Cognitive science/Psychology; [SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior
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URL: https://hal.archives-ouvertes.fr/hal-01498825
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Does writing help alphabetic readers accommodate for an ideographic system? Evidence from fMRI
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In: Proceedings of Organization of Human Brain Mapping 2015 ; https://hal.archives-ouvertes.fr/hal-01231892 ; Proceedings of Organization of Human Brain Mapping 2015, 2015, Honolulu, Unknown Region (2015)
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Functional Specificity in the Motor System: Evidence From Coupled fMRI and Kinematic Recordings During Letter and Digit Writing
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In: ISSN: 1065-9471 ; EISSN: 1097-0193 ; Human Brain Mapping ; https://hal.archives-ouvertes.fr/hal-01384071 ; Human Brain Mapping, Wiley, 2014, 35 (12), pp.6077-6087. ⟨10.1002/hbm.22606⟩ (2014)
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Problématique d'analyse et de modélisation des erreurs en production écrite. Approche interdisciplinaire (poster)
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In: 16ème Conférence sur le Traitement Automatique des Langues Naturelles (TALN 2009) ; https://hal.archives-ouvertes.fr/hal-03620121 ; 16ème Conférence sur le Traitement Automatique des Langues Naturelles (TALN 2009), LIPN (Laboratoire d’Informatique de Paris-Nord, Université Paris 13 & CNRS); ATALA, Jun 2009, Senlis, France ; https://www.atala.org/-Conference-TALN-RECITAL (2009)
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Méthodologie d'annotation des erreurs en production écrite. Principes et résultats préliminaires
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In: Actes de la 14ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs ; Journées d'Etudes sur la Parole / Traitement Automatique de la Langue Naturelle (TALN 2007) ; https://hal.archives-ouvertes.fr/hal-03624213 ; Journées d'Etudes sur la Parole / Traitement Automatique de la Langue Naturelle (TALN 2007), Jun 2007, Toulouse, France. pp.529-538 (2007)
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