The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder / Tiffany G. WOYNAROSKI in Autism Research, 10-3 (March 2017)  

Public ISBD [article]  inAutism Research > 10-3 (March 2017) . - p.508-519 Titre : The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Tiffany G. WOYNAROSKI, Auteur ; D. Kimbrough OLLER, Auteur ; Bahar KECELI-KAYSILI, Auteur ; Dongxin XU, Auteur ; Jeffrey A. RICHARDS, Auteur ; Jill GILKERSON, Auteur ; Sharmistha GRAY, Auteur ; Paul J. YODER, Auteur Article en page(s) : p.508-519 Langues : Anglais (eng) Mots-clés : useful speech  language  vocalizations  automated vocal analysis  LENA  preschool  preverbal  autism Index. décimale : PER Périodiques Résumé : Theory and research suggest that vocal development predicts “useful speech” in preschoolers with autism spectrum disorder (ASD), but conventional methods for measurement of vocal development are costly and time consuming. This longitudinal correlational study examines the reliability and validity of several automated indices of vocalization development relative to an index derived from human coded, conventional communication samples in a sample of preverbal preschoolers with ASD. Automated indices of vocal development were derived using software that is presently “in development” and/or only available for research purposes and using commercially available Language ENvironment Analysis (LENA) software. Indices of vocal development that could be derived using the software available for research purposes: (a) were highly stable with a single day-long audio recording, (b) predicted future spoken vocabulary to a degree that was nonsignificantly different from the index derived from conventional communication samples, and (c) continued to predict future spoken vocabulary even after controlling for concurrent vocabulary in our sample. The score derived from standard LENA software was similarly stable, but was not significantly correlated with future spoken vocabulary. Findings suggest that automated vocal analysis is a valid and reliable alternative to time intensive and expensive conventional communication samples for measurement of vocal development of preverbal preschoolers with ASD in research and clinical practice. En ligne : http://dx.doi.org/10.1002/aur.1667 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=304 [article] The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder [Texte imprimé et/ou numérique] / Tiffany G. WOYNAROSKI, Auteur ; D. Kimbrough OLLER, Auteur ; Bahar KECELI-KAYSILI, Auteur ; Dongxin XU, Auteur ; Jeffrey A. RICHARDS, Auteur ; Jill GILKERSON, Auteur ; Sharmistha GRAY, Auteur ; Paul J. YODER, Auteur . - p.508-519. Langues : Anglais (eng) in Autism Research > 10-3 (March 2017) . - p.508-519 Mots-clés : useful speech  language  vocalizations  automated vocal analysis  LENA  preschool  preverbal  autism Index. décimale : PER Périodiques Résumé : Theory and research suggest that vocal development predicts “useful speech” in preschoolers with autism spectrum disorder (ASD), but conventional methods for measurement of vocal development are costly and time consuming. This longitudinal correlational study examines the reliability and validity of several automated indices of vocalization development relative to an index derived from human coded, conventional communication samples in a sample of preverbal preschoolers with ASD. Automated indices of vocal development were derived using software that is presently “in development” and/or only available for research purposes and using commercially available Language ENvironment Analysis (LENA) software. Indices of vocal development that could be derived using the software available for research purposes: (a) were highly stable with a single day-long audio recording, (b) predicted future spoken vocabulary to a degree that was nonsignificantly different from the index derived from conventional communication samples, and (c) continued to predict future spoken vocabulary even after controlling for concurrent vocabulary in our sample. The score derived from standard LENA software was similarly stable, but was not significantly correlated with future spoken vocabulary. Findings suggest that automated vocal analysis is a valid and reliable alternative to time intensive and expensive conventional communication samples for measurement of vocal development of preverbal preschoolers with ASD in research and clinical practice. En ligne : http://dx.doi.org/10.1002/aur.1667 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=304

What Automated Vocal Analysis Reveals About the Vocal Production and Language Learning Environment of Young Children with Autism / Steven F. WARREN in Journal of Autism and Developmental Disorders, 40-5 (May 2010)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 40-5 (May 2010) . - p.555.569 Titre : What Automated Vocal Analysis Reveals About the Vocal Production and Language Learning Environment of Young Children with Autism Type de document : Texte imprimé et/ou numérique Auteurs : Steven F. WARREN, Auteur ; Jill GILKERSON, Auteur ; Jeffrey A. RICHARDS, Auteur ; D. Kimbrough OLLER, Auteur ; Dongxin XU, Auteur ; Umit YAPANEL, Auteur ; Sharmistha GRAY, Auteur Année de publication : 2010 Article en page(s) : p.555.569 Langues : Anglais (eng) Mots-clés : Autism Language-development Assessment Conversational-turn-taking Language-input Automated-vocal-analysis Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1007/s10803-009-0902-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=100 [article] What Automated Vocal Analysis Reveals About the Vocal Production and Language Learning Environment of Young Children with Autism [Texte imprimé et/ou numérique] / Steven F. WARREN, Auteur ; Jill GILKERSON, Auteur ; Jeffrey A. RICHARDS, Auteur ; D. Kimbrough OLLER, Auteur ; Dongxin XU, Auteur ; Umit YAPANEL, Auteur ; Sharmistha GRAY, Auteur . - 2010 . - p.555.569. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 40-5 (May 2010) . - p.555.569 Mots-clés : Autism Language-development Assessment Conversational-turn-taking Language-input Automated-vocal-analysis Index. décimale : PER Périodiques Résumé : 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. En ligne : http://dx.doi.org/10.1007/s10803-009-0902-5 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=100

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