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Simplification of literary and scientific texts to improve reading fluency and comprehension in beginning readers of French
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In: ISSN: 0142-7164 ; EISSN: 1469-1817 ; Applied Psycholinguistics ; https://hal-amu.archives-ouvertes.fr/hal-03549026 ; Applied Psycholinguistics, Cambridge University Press (CUP), 2022, pp.1-28. ⟨10.1017/S014271642100062X⟩ (2022)
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Using Virtual Reality to Assess Reading Fluency in Children
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In: ISSN: 2504-284X ; Frontiers in Education ; https://hal-amu.archives-ouvertes.fr/hal-03257346 ; Frontiers in Education , Frontiers, 2021, 6, ⟨10.3389/feduc.2021.693355⟩ (2021)
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As time goes by: space-time compatibility effects in word recognition
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In: ISSN: 0278-7393 ; EISSN: 1939-1285 ; Journal of Experimental Psychology: Learning, Memory, and Cognition ; https://hal-amu.archives-ouvertes.fr/hal-03193618 ; Journal of Experimental Psychology: Learning, Memory, and Cognition, American Psychological Association, 2021, ⟨10.1037/xlm0001007⟩ (2021)
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The dynamics of reading complex words: evidence from steady-state visual evoked potentials
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In: ISSN: 2045-2322 ; EISSN: 2045-2322 ; Scientific Reports ; https://hal-amu.archives-ouvertes.fr/hal-03320167 ; Scientific Reports, Nature Publishing Group, 2021, 11 (1), ⟨10.1038/s41598-021-95292-0⟩ (2021)
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Online activation of L1 Danish orthography enhances spoken word recognition of Swedish
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In: ISSN: 0332-5865 ; Nordic Journal of Linguistics ; https://hal-amu.archives-ouvertes.fr/hal-03283527 ; Nordic Journal of Linguistics, 2021, pp.1-19. ⟨10.1017/S0332586521000056⟩ (2021)
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Neural processing of vision and language in kindergarten is associated with prereading skills and predicts future literacy
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In: ISSN: 1065-9471 ; EISSN: 1097-0193 ; Human Brain Mapping ; https://hal-amu.archives-ouvertes.fr/hal-03217489 ; Human Brain Mapping, Wiley, 2021, ⟨10.1002/hbm.25449⟩ (2021)
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Neural processing of vision and language in kindergarten is associated with prereading skills and predicts future literacy ...
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Alector: A Parallel Corpus of Simplified French Texts with Alignments of Misreadings by Poor and Dyslexic Readers
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In: Language Resources and Evaluation for Language Technologies (LREC) ; https://hal.archives-ouvertes.fr/hal-02503986 ; Language Resources and Evaluation for Language Technologies (LREC), May 2020, Marseille, France (2020)
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Orthographic consistency influences morphological processing in reading aloud: Evidence from a cross‐linguistic study
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In: ISSN: 1363-755X ; EISSN: 1467-7687 ; Developmental Science ; https://hal-amu.archives-ouvertes.fr/hal-02507581 ; Developmental Science, Wiley, 2020, ⟨10.1111/desc.12952⟩ (2020)
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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
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In: ISSN: 0963-7214 ; EISSN: 1467-8721 ; Current Directions in Psychological Science ; https://hal-amu.archives-ouvertes.fr/hal-02566111 ; Current Directions in Psychological Science, Association for Psychological Science, 2020, pp.096372142091587. ⟨10.1177/0963721420915873⟩ (2020)
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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
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In: Current Directions in Psychological Science, Vol. 29, no. 3 (Jun 2020), pp. 293-300 (2020)
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Learning to Read and Dyslexia: From Theory to Intervention Through Personalized Computational Models
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In: Curr Dir Psychol Sci (2020)
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Orthographic consistency influences morphological processing in reading aloud: Evidence from a cross-linguistic study
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Frequency-tagged visual evoked responses track syllable effects in visual word recognition
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In: ISSN: 0010-9452 ; Cortex ; https://hal-amu.archives-ouvertes.fr/hal-02281144 ; Cortex, Elsevier, 2019, 121, pp.60-77. ⟨10.1016/j.cortex.2019.08.014⟩ (2019)
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Modeling the Variability of Developmental Dyslexia
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In: Developmental Dyslexia across Languages and Writing Systems ; https://hal-amu.archives-ouvertes.fr/hal-02308934 ; Developmental Dyslexia across Languages and Writing Systems, Cambridge University Press, pp.350-371, 2019, ⟨10.1017/9781108553377.016⟩ (2019)
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Understanding Dyslexia Through Personalized Large-Scale Computational Models ...
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Understanding Dyslexia Through Personalized Large-Scale Computational Models ...
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Understanding dyslexia through personalized large-scale computational models
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In: Psychological Science, Vol. 30, no. 3 (Feb 2019), pp. 386-395 (2019)
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Modeling the variability of developmental dyslexia
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In: Developmental dyslexia across languages and writing systems / Ludo Verhoeven, Charles Perfetti and Kenneth Pugh (eds.), pp. 350-371 (2019)
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Abstract:
Reading is a highly complex task that relies on the integration of visual, orthographic, phonological and semantic information. This complexity is clearly reflected in current computational models of reading (Coltheart et al., 2001; Harm & Seidenberg, 1999, 2004; Perry, Ziegler, & Zorzi, 2007, 2010; Plaut et al., 1996). These models specify the “ingredients” of the reading process in a precise and detailed fashion as they implement the units and computations that are necessary to go from the visual information to word recognition and word production. Such models make it possible to simulate real reading performance in terms of reading latencies (how long it takes to compute the pronunciation of a word or pseudoword) and reading accuracy (whether the output of the model is correct). Computational models are particularly well suited to helping us understand reading impairments, such as developmental or acquired dyslexia.
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URL: http://hdl.handle.net/1959.3/459515 https://doi.org/10.1017/9781108553377.016
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Understanding Dyslexia Through Personalized Large-Scale Computational Models
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