4.6 Article

Expressive visual text-to-speech as an assistive technology for individuals with autism spectrum conditions

期刊

COMPUTER VISION AND IMAGE UNDERSTANDING
卷 148, 期 -, 页码 193-200

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.cviu.2015.08.011

关键词

Autism spectrum conditions; Emotion recognition; Social cognition; Intervention; Assistive technology

资金

  1. Erasmus
  2. Centre for Psychology, Behaviour and Achievement, Coventry University, UK
  3. Autism Research Trust
  4. Medical Research Council UK
  5. National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care East of England at Cambridgeshire and Peterborough NHS Foundation Trust
  6. MRC [G0600977] Funding Source: UKRI
  7. Medical Research Council [G0600977] Funding Source: researchfish

向作者/读者索取更多资源

Adults with Autism Spectrum Conditions (ASC) experience marked difficulties in recognising 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. (C) 2015 The Authors. Published by Elsevier Inc.

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