2016/08/08 by Riccardo Fusaroli, Anna Lambrechts, Dan Bang +2 · 1 voice · 3 citations
Neuroscience · Psychology · Social Sciences · #Autism Spectrum Disorder Research #Language Development and Disorders #Child Development and Digital Technology
paper · pdf · doi:10.1002/aur.1678
openalex publication_date 2016/08/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/03
Individuals with Autism Spectrum Disorder (ASD) tend to show distinctive, atypical acoustic patterns of speech. These behaviors affect social interactions and social development and could represent a non-invasive marker for ASD. We systematically reviewed the literature quantifying acoustic patterns in ASD. Search terms were: (prosody OR intonation OR inflection OR intensity OR pitch OR fundamental frequency OR speech rate OR voice quality OR acoustic) AND (autis* OR Asperger). Results were filtered to include only: empirical studies quantifying acoustic features of vocal production in ASD, with a sample size >2, and the inclusion of a neurotypical comparison group and/or correlations between acoustic measures and severity of clinical features. We identified 34 articles, including 30 univariate studies and 15 multivariate machine-learning studies. We performed meta-analyses of the univariate studies, identifying significant differences in mean pitch and pitch range between individuals with ASD and comparison participants (Cohen's d of 0.4-0.5 and discriminatory accuracy of about 61-64%). The multivariate studies reported higher accuracies than the univariate studies (63-96%). However, the methods used and the acoustic features investigated were too diverse for performing meta-analysis. We conclude that multivariate studies of acoustic patterns are a promising but yet unsystematic avenue for establishing ASD markers. We outline three recommendations for future studies: open data, open methods, and theory-driven research. Autism Res 2017, 10: 384-407. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.