Predicting speech intelligibility with a multiple speech subsystems approach in children with cerebral palsy

Jimin Lee, Katherine C. Hustad, Gary Weismer

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Results: Multiple acoustic variables reflecting the articulatory subsystem were different in the SMI group, compared to the NSMI and typically developing groups. A significant speech intelligibility prediction model was obtained with all variables entered into the model (adjusted R2= .801). The articulatory subsystem showed the most substantial independent contribution (58%) to speech intelligibility. Incremental R2 analyses revealed that any single variable explained less than 9% of speech intelligibility variability.

Method: Nine acoustic variables reflecting different subsystems, and speech intelligibility, were measured in 22 children with CP. These children included 13 with a clinical diagnosis of dysarthria (speech motor impairment [SMI] group) and 9 judged to be free of dysarthria (no SMI [NSMI] group). Data from children with CP were compared to data from age-matched typically developing children.

Conclusions: Children in the SMI group had articulatory subsystem problems as indexed by acoustic measures. As in the adult literature, the articulatory subsystem makes the primary contribution to speech intelligibility variance in dysarthria, with minimal or no contribution from other systems.

Purpose: Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems.

Original languageEnglish (US)
Pages (from-to)1666-1678
Number of pages13
JournalJournal of Speech, Language, and Hearing Research
Volume57
Issue number5
DOIs
StatePublished - Oct 1 2014

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Speech Intelligibility
Cerebral Palsy
subsystem
Acoustics
Dysarthria
acoustics
Speech Acoustics
Group
Impairment

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language
  • Speech and Hearing

Cite this

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title = "Predicting speech intelligibility with a multiple speech subsystems approach in children with cerebral palsy",
abstract = "Results: Multiple acoustic variables reflecting the articulatory subsystem were different in the SMI group, compared to the NSMI and typically developing groups. A significant speech intelligibility prediction model was obtained with all variables entered into the model (adjusted R2= .801). The articulatory subsystem showed the most substantial independent contribution (58{\%}) to speech intelligibility. Incremental R2 analyses revealed that any single variable explained less than 9{\%} of speech intelligibility variability.Method: Nine acoustic variables reflecting different subsystems, and speech intelligibility, were measured in 22 children with CP. These children included 13 with a clinical diagnosis of dysarthria (speech motor impairment [SMI] group) and 9 judged to be free of dysarthria (no SMI [NSMI] group). Data from children with CP were compared to data from age-matched typically developing children.Conclusions: Children in the SMI group had articulatory subsystem problems as indexed by acoustic measures. As in the adult literature, the articulatory subsystem makes the primary contribution to speech intelligibility variance in dysarthria, with minimal or no contribution from other systems.Purpose: Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems.",
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Predicting speech intelligibility with a multiple speech subsystems approach in children with cerebral palsy. / Lee, Jimin; Hustad, Katherine C.; Weismer, Gary.

In: Journal of Speech, Language, and Hearing Research, Vol. 57, No. 5, 01.10.2014, p. 1666-1678.

Research output: Contribution to journalArticle

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