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Journal of Autism and Developmental Disorders
Gepubliceerd in: Journal of Autism and Developmental Disorders 5/2010

01-05-2010 | Original Paper

What Automated Vocal Analysis Reveals About the Vocal Production and Language Learning Environment of Young Children with Autism

Auteurs: Steven F. Warren, Jill Gilkerson, Jeffrey A. Richards, D. Kimbrough Oller, Dongxin Xu, Umit Yapanel, Sharmistha Gray

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 5/2010

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Abstract

The study compared the vocal production and language learning environments of 26 young children with autism spectrum disorder (ASD) to 78 typically developing children using measures derived from automated vocal analysis. A digital language processor and audio-processing algorithms measured the amount of adult words to children and the amount of vocalizations they produced during 12-h recording periods in their natural environments. The results indicated significant differences between typically developing children and children with ASD in the characteristics of conversations, the number of conversational turns, and in child vocalizations that correlated with parent measures of various child characteristics. Automated measurement of the language learning environment of young children with ASD reveals important differences from the environments experienced by typically developing children.
vorige artikel Pre-Eclampsia, Birth Weight, and Autism Spectrum Disorders
volgende artikel The TEACCH Program in the Era of Evidence-Based Practice
Voetnoten
1
Participants with an echolalia diagnosis were excluded from the current study because their frequent repetition of words or phrases could inflate the estimates for automatic vocalization counts and conversational turn counts without reflecting advanced language skills or meaningful interactions.
 
2
We repeated the analyses presented here matching instead on number of sessions to substantively similar results.
 
3
Within-conversation child vocalizations (defined in the LENA Automated Language Measures section) were significantly less variable with respect to duration in the ASD sample (SD = 0.7 s) than in the TD sample (SD = 1.7 s), Levene Test F = 9.02, p < .01. All other comparisons were nonsignificant with p > .05.
 
4
See Ford et al. (2008) for detailed information on the DLP hardware and audio recording specifications. Note that the LENA language analysis segmentation process has been simplified here and is described in more detail in Xu et al. (2008b).
 
5
See Xu et al. (2008a) for more detail regarding the 70 test set files, and see Gilkerson et al. (2008) for information about inter-rater transcription reliability.
 
6
Standardized percentile values for all measures were referenced to the original normative sample from the LENA Foundation Natural Language Study described previously.
 
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Metagegevens
Titel
What Automated Vocal Analysis Reveals About the Vocal Production and Language Learning Environment of Young Children with Autism
Auteurs
Steven F. Warren
Jill Gilkerson
Jeffrey A. Richards
D. Kimbrough Oller
Dongxin Xu
Umit Yapanel
Sharmistha Gray
Publicatiedatum
01-05-2010
Uitgeverij
Springer US
Gepubliceerd in
Journal of Autism and Developmental Disorders / Uitgave 5/2010
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI
https://doi.org/10.1007/s10803-009-0902-5

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