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Bilingual Language Development in Infancy: What Can We Do to Support Bilingual Families?
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In: Policy Insights Behav Brain Sci (2022)
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Is there a bilingual disadvantage for word segmentation? A computational modeling approach
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In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498905 ; Journal of Child Language, Cambridge University Press (CUP), 2021, pp.1-28. ⟨10.1017/S0305000921000568⟩ (2021)
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Abstract:
International audience ; Abstract Since there are no systematic pauses delimiting words in speech, the problem of word segmentation is formidable even for monolingual infants. We use computational modeling to assess whether word segmentation is substantially harder in a bilingual than a monolingual setting. Seven algorithms representing different cognitive approaches to segmentation are applied to transcriptions of naturalistic input to young children, carefully processed to generate perfectly matched monolingual and bilingual corpora. We vary the overlap in phonology and lexicon experienced by modeling exposure to languages that are more similar (Catalan and Spanish) or more different (English and Spanish). We find that the greatest variation in performance is due to different segmentation algorithms and the second greatest to language, with bilingualism having effects that are smaller than both algorithm and language effects. Implications of these computational results for experimental and modeling approaches to language acquisition are discussed.
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Keyword:
[SCCO.LING]Cognitive science/Linguistics; [SCCO.PSYC]Cognitive science/Psychology; computational modeling; infancy; word segmentation
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URL: https://doi.org/10.1017/S0305000921000568
https://hal.archives-ouvertes.fr/hal-03498905/file/2021_Fibla_JCL.pdf
https://hal.archives-ouvertes.fr/hal-03498905/document
https://hal.archives-ouvertes.fr/hal-03498905
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SM: Bilingual language development in infancy: What can we do to support bilingual families? ...
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SM to: Is there a bilingual disadvantage for word segmentation? A computational modeling approach ...
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WordSeg: Standardizing unsupervised word form segmentation from text
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WordSeg: Standardizing unsupervised word form segmentation from text
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In: ISSN: 1554-351X ; EISSN: 1554-3528 ; Behavior Research Methods ; https://hal.archives-ouvertes.fr/hal-02274072 ; Behavior Research Methods, Psychonomic Society, Inc, 2019, ⟨10.3758/s13428-019-01223-3⟩ (2019)
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Learning homophones in context: Easy cases are favored in the lexicon of natural languages
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In: ISSN: 0010-0285 ; EISSN: 1095-5623 ; Cognitive Psychology ; https://hal.archives-ouvertes.fr/hal-02105022 ; Cognitive Psychology, Elsevier, 2018, 104, pp.83-105. ⟨10.1016/j.cogpsych.2018.04.001⟩ (2018)
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