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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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Abstract:
International audience ; In this paper, we present a new parallel corpus addressed to researchers, teachers, and speech therapists interested in text simplification as a means of alleviating difficulties in children learning to read. The corpus is composed of excerpts drawn from 79 authentic literary (tales, stories) and scientific (documentary) texts commonly used in French schools for children aged between 7 to 9 years old. The excerpts were manually simplified at the lexical, morpho-syntactic, and discourse levels in order to propose a parallel corpus for reading tests and for the development of automatic text simplification tools. A sample of 21 poor-reading and dyslexic children with an average reading delay of 2.5 years read a portion of the corpus. The transcripts of readings errors were integrated into the corpus with the goal of identifying lexical difficulty in the target population. By means of statistical testing, we provide evidence that the manual simplifications significantly reduced reading errors, highlighting that the words targeted for simplification were not only well-chosen but also substituted with substantially easier alternatives. The entire corpus is available for consultation through a web interface and available on demand for research purposes.
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Keyword:
[SHS.EDU]Humanities and Social Sciences/Education; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [SHS.STAT]Humanities and Social Sciences/Methods and statistics; dyslexia; linguistic complexity; misreading; Parallel corpora; poor-readers; readability; text simplification
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URL: https://hal.archives-ouvertes.fr/hal-02503986/file/LREC_2020_ALECTOR_Corpus-final_10032020.pdf https://hal.archives-ouvertes.fr/hal-02503986 https://hal.archives-ouvertes.fr/hal-02503986/document
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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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Understanding Dyslexia Through Personalized Large-Scale Computational Models
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