"Is voice a marker for Autism spectrum disorder? A systematic review and meta‐analysis". Issue 3 (8th August 2016)

• Record Type: Journal Article
• Authors: Fusaroli, Riccardo; Lambrechts, Anna; Bang, Dan; Bowler, Dermot M.; Gaigg, Sebastian B.
• Is Part Of: Autism research. Volume 10:Issue 3(2017)
• Page Start: 384
• Page End: 407
• Publication Date: 2016-08-08
• Subjects: voice -- speech -- acoustic properties -- machine learning -- biomarker; Autism -- Periodicals; Autism -- Research -- Periodicals; 616.85882005
• DOI: 10.1002/aur.1678
• Languages: English
• ISSNs: 1939-3792

Abstract

Abstract : 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.