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

被引：21

作者：

Cassidy, S. A. ^{[1
,3
]}

Stenger, B. ^{[2
]}

Van Dongen, L. ^{[4
]}

Yanagisawa, K. ^{[2
]}

Anderson, R. ^{[3
,5
]}

Wan, V. ^{[3
,5
]}

Baron-Cohen, S. ^{[3
,5
]}

Cipolla, R. ^{[2
,6
]}

机构：

[1] Coventry Univ, Ctr Psychol Behav & Achievement, Coventry CV1 5FB, W Midlands, England

[2] Toshiba Res Europe Ltd, 208 Sci Pk, Cambridge CB4 0GZ, England

[3] Univ Cambridge, Dept Psychiat, Autism Res Ctr, Douglas House,18B Trumpington Rd, Cambridge CB2 BAH, England

[4] Maastricht Univ, Fac Psychol, NL-6200 MD Maastricht, Netherlands

[5] Cambridgeshire & Peterborough Fdn NHS Trust, CLASS Clin, Cambridge, England

[6] Univ Cambridge, Dept Engn, Cambridge CB2 1PZ, England

来源：

COMPUTER VISION AND IMAGE UNDERSTANDING | 2016年 / 148卷

基金：

英国医学研究理事会;

关键词：

Autism spectrum conditions; Emotion recognition; Social cognition; Intervention; Assistive technology; EMOTION RECOGNITION; FUNCTIONING AUTISM; SOCIAL INFORMATION; ADULTS; CHILDREN; FACES; ATTENTION; DISORDERS; COGNITION; MIND;

D O I：

10.1016/j.cviu.2015.08.011

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：193 / 200

页数：8