What automated vocal analysis reveals about the vocal production and language learning environment of young children with autism.
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.
Warren
Steven F
SF
Institute for Life Span Studies, University of Kansas, Lawrence, 66045-7555, USA. sfwarren@ku.edu
Gilkerson
Jill
J
Richards
Jeffrey A
JA
Oller
D Kimbrough
DK
Xu
Dongxin
D
Yapanel
Umit
U
Gray
Sharmistha
S
D000328:Adult; D000465:Algorithms; D016022:Case-Control Studies; D002659:Child Development Disorders, Pervasive / Q000175:diagnosis / Q000523:psychology*; D002663:Child Language; D002675:Child, Preschool; D005190:Family; D005260:Female; D006801:Humans; D007223:Infant; D007807:Language Tests; D008297:Male; D013060:Speech; D013061:Speech Acoustics; D013068:Speech Production Measurement / Q000379:methods; D013997:Time Factors; D014706:Verbal Learning; D014825:Vocabulary