Expressive Visual Text-To-Speech as an Assistive Technology for Individuals with Autism Spectrum Conditions

S. Cassidy, B. Stenger, L. Van Dongen, K. Yanagisawa, R. Anderson, V. Wan, S. Baron-Cohen, R. Cipolla

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    Adults with Autism Spectrum Conditions (ASC) experience marked difficulties in recognizing the emotions of others and responding appropriately. The clinical characteristics of ASC mean that face to face or group interventions may not be appropriate for this clinical group. This article explores the potential of a new interactive technology, converting text to emotionally expressive speech, to improve emotion processing ability and attention to faces in adults with ASC. We demonstrate a method for generating a near-videorealistic avatar (XpressiveTalk), which can produce a video of a face uttering inputted text, in a large variety of emotional tones. We then demonstrate that general population adults can correctly recognize the emotions portrayed by XpressiveTalk. Adults with ASC are significantly less accurate than controls, but still above chance levels for inferring emotions from XpressiveTalk. Both groups are significantly more accurate when inferring sad emotions from XpressiveTalk compared to the original actress, and rate these expressions as significantly more preferred and realistic. The potential applications for XpressiveTalk as an assistive technology for adults with ASC is discussed.
    Original languageEnglish
    Pages (from-to)193-200
    JournalComputer Vision and Image Understanding
    Early online date27 May 2016
    Publication statusPublished - Jul 2016

    Bibliographical note

    Open Access funded by Medical Research Council

    Under a Creative Commons license


    • Autism Spectrum Conditions
    • Emotion Recognition
    • Social Cognition
    • Intervention
    • Assistive Technology

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