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1
A computationally-based approach to the understanding of child's phonological development
In: 50th Poznan Linguistic Meeting http://wa.amu.edu.pl/plm/2020/files/posters/Briglia_PLM2021_Poster.pdf ; https://hal.archives-ouvertes.fr/hal-03445409 ; 50th Poznan Linguistic Meeting http://wa.amu.edu.pl/plm/2020/files/posters/Briglia_PLM2021_Poster.pdf, Sep 2021, Poznan, Poland (2021)
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2
Deux méthodes d’extraction automatique des connaissances pour essayer de comprendre la structuration de la conscience phonologique chez l’enfant
In: 18e Rencontres du Réseau Français de Phonologie ; https://hal.archives-ouvertes.fr/hal-03162037 ; 18e Rencontres du Réseau Français de Phonologie, Jul 2021, Clermont-Ferrand, France (2021)
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3
A new interactive graphical approach to vizualise children phoneme’s acquisition over time
In: Phonetics and Phonology in Europe 2021 ; https://hal.archives-ouvertes.fr/hal-03565898 ; Phonetics and Phonology in Europe 2021, Jun 2021, Barcelona, Spain (2021)
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4
Visualizing cluster of words: a graphical approach to grammar acquisition
In: CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS 13th Scientific Meeting of the Classification and Data Analysis Group - Firenze, September 9-11, 2021 ; https://hal.archives-ouvertes.fr/hal-03320170 ; Giovanni C. Porzio; Carla Rampichini; Chiara Bocci. CLADAG 2021 BOOK OF ABSTRACTS AND SHORT PAPERS 13th Scientific Meeting of the Classification and Data Analysis Group - Firenze, September 9-11, 2021, Firenze University Press, pp.392-395, 2021, 978-88-5518-340-6. ⟨10.36253/978-88-5518-340-6⟩ (2021)
Abstract: International audience ; Language has been traditionally considered as a qualitative phenomenon that mainly requires hermeneutical methodologies in order to be studied, yet in recent decades thanks to advances in data storage, processing and visualization - there has been a growing and fertile interest in analysing language by relying on statistics and quantitative methods. In light of these motivations, we think it is worthwhile to try to explore databases made up of transcripted infant children spoken language in order to verify whether and how underlying patterns and recurrent sequences of learning stages work during acquisition. So, we think that the Expectation Maximization clustering method combined with an innovative graphical visualization can be useful to evaluate the development of linguistic structures over time in a reliable way.
Keyword: [SHS]Humanities and Social Sciences; EM clustering; first language acquisition; graphical visualization; phonetic variation rate; POS Tags
URL: https://hal.archives-ouvertes.fr/hal-03320170/document
https://hal.archives-ouvertes.fr/hal-03320170/file/19407%20pages%20392%20-%20395.pdf
https://doi.org/10.36253/978-88-5518-340-6
https://hal.archives-ouvertes.fr/hal-03320170
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5
A logistic regression model for predicting child language performance ; Un modèle de régression logistique pour la prédiction du développement langagier chez l'enfant
In: SIS 2021, 50th Annuale Conference of the Italian Statistical Society" ; https://hal.archives-ouvertes.fr/hal-03318721 ; SIS 2021, 50th Annuale Conference of the Italian Statistical Society", Jun 2021, Pise, Italy (2021)
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6
Model-based clustering and first language acquisition ; Clustering basé sur des modèles et acquisition du langage
In: Book of Short Papers of the 5th international workshop onModels and Learning for Clustering and Classification MBC2 2020, Catania, Italy ; https://hal.archives-ouvertes.fr/hal-03444191 ; Book of Short Papers of the 5th international workshop on Models and Learning for Clustering and Classification MBC2 2020, Catania, Italy, 2021 (2021)
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7
Classification des catégories grammaticales sur deux corpus longitudinaux d’enfants
In: Actes des 2èmes journées scientifiques du Groupement de Recherche Linguistique Informatique Formelle et de Terrain (LIFT). ; 2èmes journées scientifiques du Groupement de Recherche Linguistique Informatique Formelle et de Terrain (LIFT) ; https://hal.archives-ouvertes.fr/hal-03047149 ; 2èmes journées scientifiques du Groupement de Recherche Linguistique Informatique Formelle et de Terrain (LIFT), 2020, Montrouge, France. pp.23-33 (2020)
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8
Data mining and child phonological acquisition: a case study
In: 15th Language at the University of Essex Postgraduate Conference ; https://hal.archives-ouvertes.fr/hal-03565935 ; 15th Language at the University of Essex Postgraduate Conference, Jun 2020, Colchester, United Kingdom (2020)
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9
Mining longitudinal corpus of spontaneous speech: a graph-based approach to child phonetic variation
In: 41st Annual Meeting of the Department of Linguistics ; https://hal.archives-ouvertes.fr/hal-03162014 ; 41st Annual Meeting of the Department of Linguistics, May 2020, Thessaloniki, Greece (2020)
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10
Reinterpreting first language acquisition through data mining: a case study
In: Manchester Forum in Linguistics 2020 ; https://hal.archives-ouvertes.fr/hal-03565920 ; Manchester Forum in Linguistics 2020, Apr 2020, Manchester, United Kingdom (2020)
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11
Classification des catégories grammaticales sur un corpus longitudinal d’enfant
In: 2e Journées GdR LIFT, Linguistique Informatique Formelle et de Terrain ; https://hal.archives-ouvertes.fr/hal-03159882 ; 2e Journées GdR LIFT, Linguistique Informatique Formelle et de Terrain, Dec 2020, Nancy, France. pp.28-38 ; https://bul.univ-lorraine.fr/index.php/s/AcbswRNMgs4qQb6 (2020)
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12
Identify the speech code through statistic: a data driven approach
In: 50th Scientific Meeting of the Italian Statistical Society SIS 2020 ; https://hal.archives-ouvertes.fr/hal-03161969 ; 50th Scientific Meeting of the Italian Statistical Society SIS 2020, Jun 2020, Pise, Italy (2020)
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13
Data mining and first language acquisition: a case study of a French corpus
In: UK Cognitive Linguistic Conference 2020 ; https://hal.archives-ouvertes.fr/hal-03162007 ; UK Cognitive Linguistic Conference 2020, Jul 2020, Birmingham, United Kingdom (2020)
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