Latent Semantic Analysis Discriminates Children with Developmental Language Disorder (DLD) from Children with Typical Language Development

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Abstract

Computer 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.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • Karolinska University Hospital
  • Karolinska Institute
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Jämförande språkvetenskap och lingvistik

Nyckelord

Originalspråkengelska
TidskriftJournal of Psycholinguistic Research
StatusE-pub ahead of print - 2019 jan 25
PublikationskategoriForskning
Peer review utfördJa