Lisa D Yankowitz1,2, Robert T Schultz3,4,5, Julia Parish-Morris3,4. 1. Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA. lisayank@sas.upenn.edu. 2. Department of Psychology, University of Pennsylvania, 3720 Walnut Street, Philadelphia, PA, 19104, USA. lisayank@sas.upenn.edu. 3. Center for Autism Research, Children's Hospital of Philadelphia, 2716 South St, Philadelphia, PA, 19104, USA. 4. Department of Psychiatry, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA. 5. Department of Pediatrics, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA, 19105, USA.
Abstract
PURPOSE OF REVIEW: We review what is known about how pre-linguistic vocal differences in autism spectrum disorder (ASD) unfold across development and consider whether vocalization features can serve as useful diagnostic indicators. RECENT FINDINGS: Differences in the frequency and acoustic quality of several vocalization types (e.g., babbles and cries) during the first year of life are associated with later ASD diagnosis. Paralinguistic features (e.g., prosody) measured during early and middle childhood can accurately classify current ASD diagnosis using cross-validated machine learning approaches. Pre-linguistic vocalization differences in infants are promising behavioral markers of later ASD diagnosis. In older children, paralinguistic features hold promise as diagnostic indicators as well as clinical targets. Future research efforts should focus on (1) bridging the gap between basic research and practical implementations of early vocalization-based risk assessment tools, and (2) demonstrating the clinical impact of targeting atypical vocalization features during social skill interventions for older children.
PURPOSE OF REVIEW: We review what is known about how pre-linguistic vocal differences in autism spectrum disorder (ASD) unfold across development and consider whether vocalization features can serve as useful diagnostic indicators. RECENT FINDINGS: Differences in the frequency and acoustic quality of several vocalization types (e.g., babbles and cries) during the first year of life are associated with later ASD diagnosis. Paralinguistic features (e.g., prosody) measured during early and middle childhood can accurately classify current ASD diagnosis using cross-validated machine learning approaches. Pre-linguistic vocalization differences in infants are promising behavioral markers of later ASD diagnosis. In older children, paralinguistic features hold promise as diagnostic indicators as well as clinical targets. Future research efforts should focus on (1) bridging the gap between basic research and practical implementations of early vocalization-based risk assessment tools, and (2) demonstrating the clinical impact of targeting atypical vocalization features during social skill interventions for older children.
Entities:
Keywords:
Acoustic properties; Autism; Early diagnosis; Paralinguistics; Prosody; Speech production
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