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Autor/inn/enBååth, Rasmus; Sikström, Sverker; Kalnak, Nelli; Hansson, Kristina; Sahlén, Birgitta
TitelLatent Semantic Analysis Discriminates Children with Developmental Language Disorder (DLD) from Children with Typical Language Development
QuelleIn: Journal of Psycholinguistic Research, 48 (2019) 3, S.683-697 (15 Seiten)
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ZusatzinformationORCID (Hansson, Kristina)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0090-6905
DOI10.1007/s10936-018-09625-8
SchlagwörterSemantics; Computational Linguistics; Language Impairments; Language Acquisition; Identification; Oral Language; Comparative Analysis; Children
AbstractComputer based analyses offer a possibility for objective methods to assess semantic-linguistic quality of narratives at the text level. The aim of the present study is to investigate whether a semantic language impairment index (SELIMI) based on latent semantic analysis (LSA) can discriminate between children with developmental language disorder (DLD) and children with typical language development. Spoken narratives from 54 children with DLD and 54 age matched controls with typical language development were summarized in a semantic representation generated using LSA. A statistical model was trained to discriminate between children with DLD and children with typical language development, given the semantic vector representing each individual child's narrative. The results show that SELIMI could distinguish between children with DLD and children with typical language development significantly better than chance and thus has a potential to complement traditional analyses focussed on form or on the word level. (As Provided).
AnmerkungenSpringer. Available from: Springer Nature. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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