Quantification of speech and synchrony in the conversation of adults with autism spectrum disorder
Autoři:
Keiko Ochi aff001; Nobutaka Ono aff002; Keiho Owada aff003; Masaki Kojima aff003; Miho Kuroda aff003; Shigeki Sagayama aff004; Hidenori Yamasue aff005
Působiště autorů:
School of Media Science, Tokyo University of Technology, Hachioji, Japan
aff001; Department of Computer Science, Graduate School of Systems Design, Tokyo Metropolitan University, Hino, Japan
aff002; Department of Child Psychiatry, School of Medicine, The University of Tokyo, Tokyo, Japan
aff003; University of Tokyo, Tokyo, Japan
aff004; Department of Psychiatry, Hamamatsu University School of Medicine, Hamamatsu, Japan
aff005
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0225377
Souhrn
Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by impairments in social reciprocity and communication together with restricted interest and stereotyped behaviors. The Autism Diagnostic Observation Schedule (ADOS) is considered a ‘gold standard’ instrument for diagnosis of ASD and mainly depends on subjective assessments made by trained clinicians. To develop a quantitative and objective surrogate marker for ASD symptoms, we investigated speech features including F0, speech rate, speaking time, and turn-taking gaps, extracted from footage recorded during a semi-structured socially interactive situation from ADOS. We calculated not only the statistic values in a whole session of the ADOS activity but also conducted a block analysis, computing the statistical values of the prosodic features in each 8s sliding window. The block analysis identified whether participants changed volume or pitch according to the flow of the conversation. We also measured the synchrony between the participant and the ADOS administrator. Participants with high-functioning ASD showed significantly longer turn-taking gaps and a greater proportion of pause time, less variability and less synchronous changes in blockwise mean of intensity compared with those with typical development (TD) (p<0.05 corrected). In addition, the ASD group had significantly wider distribution than the TD group in the within-participant variability of blockwise mean of log F0 (p<0.05 corrected). The clinical diagnosis could be discriminated using the speech features with 89% accuracy. The features of turn-taking and pausing were significantly correlated with deficits of ASD in reciprocity (p<0.05 corrected). Additionally, regression analysis provided 1.35 of mean absolute error in the prediction of deficits in reciprocity, to which the synchrony of intensity especially contributed. The findings suggest that considering variance of speech features, interaction and synchrony with conversation partner are critical to characterize atypical features in the conversation of people with ASD.
Klíčová slova:
Autism – Autism spectrum disorder – Diagnostic medicine – Emotions – Regression analysis – Social communication – Speech – Verbal communication
Zdroje
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PLOS One
2019 Číslo 12
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