Rethinking Prosody Production in Autism: Nuanced Insights from Individual Differences and Network Analysis Approaches

Purpose: Prosodic differences between autistic and non-autistic individuals are recognized, but there is a lack of consensus on the specific prosodic features that characterize the “autistic voice” due to widespread heterogeneity and mixed findings. This study seeks to build further understanding of the nuances of prosody in autism through individual differences and network analyses.Method: Acoustic analyses were conducted from 66 school-age autistic and non-autistic children and adolescents’ narrative generation. Between-group analyses of pitch and timing-related prosodic features were conducted, followed by within-group analyses to investigate associations between prosodic features and individual differences in overall language skills. Thereafter, established network analysis methods (Weed et al., 2023) were adopted to detect communities of participants based on similar prosodic features.Results: Initial between-group analyses revealed that autistic participants demonstrated greater pitch range and variation, as well as slower speech and articulation rates, compared to non-autistic peers. Subsequent analyses revealed that speech and articulation rates were associated with overall language skills. In line with previous findings, the community detection algorithm identified three clusters of participants: one with more autistic participants, one with more non-autistic participants, and one with largely equal representation of autistic and non-autistic participants.Conclusions: Although between-group differences consistent with similar previous literature have been indicated, community detection analyses further support the notion that prosody in autism may be “different in different ways” (Weed et al., 2023). This work highlights the importance of moving beyond group-difference approaches in uncovering nuances to individual differences in prosody via within-group and data-driven analysis approaches.