ArticleLanguage learning and development : the official journal of the Society for Language Development2024
Different in different ways: A network-analysis approach to voice and prosody in Autism Spectrum Disorder.
Article in Language learning and development : the official journal of the Society for Language Development, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Rethinking Prosody Production in Autism: Nuanced Insights From Individual Differences and Network Analysis Approaches.Journal of speech, language, and hearing research : JSLHR · 2026Article
- Right-Hemispheric White Matter Organization Is Associated With Speech Timing in Autistic Children.Journal of speech, language, and hearing research : JSLHR · 2025Article
- Investigating frank autism: clinician initial impressions and autism characteristics.Molecular autism · 2024Article
- Repeat After Me? Both Children With and Without Autism Commonly Align Their Language With That of Their Caregivers.Cognitive science · 2023Article
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Authors and funding
4 authors.
Funding
Abstract
The current study investigated whether the difficulty in finding group differences in prosody between speakers with autism spectrum disorder (ASD) and neurotypical (NT) speakers might be explained by identifying different acoustic profiles of speakers which, while still perceived as atypical, might be characterized by different acoustic qualities. We modelled the speech from a selection of speakers (N = 26), with and without ASD, as a network of nodes defined by acoustic features. We used a community-detection algorithm to identify clusters of speakers who were acoustically similar and compared these clusters with atypicality ratings by naïve and expert human raters. Results identified three clusters: one primarily composed of speakers with ASD, one of mostly NT speakers, and one comprised of an even mixture of ASD and NT speakers. The human raters were highly reliable at distinguishing speakers with and without ASD, regardless of which cluster the speaker was in. These results suggest that community-detection methods using a network approach may complement commonly-employed human ratings to improve our understanding of the intonation profiles in ASD.
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Registered trials
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