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Ethan Weed

Non linear analyses of speech and prosody in Asperger's syndrome

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It is widely acknowledged that people on the ASD spectrum behave atypically in the way they modulate aspects of speech and voice, including pitch, fluency, and voice quality. ASD speech has been described at times as “odd”, “mechanical”, or “monotone”. However, it has proven difficult to quantify and explain this oddness of speech pattern. In this project, we quantify how the speech patterns of people with Asperger’s Syndrome (AS) differ from that of matched controls. To do so, we employed both traditional measures (pitch range and standard deviation, pause duration, and so on) and 2) non-linear techniques measuring the structure (regularity and complexity) of verbal, prosodic and fluency behaviour. Our aims were (1) to achieve a more fine-grained understanding of the speech patterns in AS than has previously been achieved using traditional, linear measures of prosody and fluency, and (2) to employ the results in a supervised machine-learning process to classify speech production as either belonging to the control or the AS group as well as to assess the severity of the disorder (as measured by Autism Spectrum Quotient), based solely on acoustic features.
Original languageEnglish
Publication year2013
Publication statusPublished - 2013
EventInternational Meeting For Autism Research - San Sebastian, Spain
Duration: 1 May 20134 May 2013

Conference

ConferenceInternational Meeting For Autism Research
CountrySpain
CitySan Sebastian
Period01/05/201304/05/2013

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