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富有表现力的视觉文本转语音技术作为自闭症谱系障碍患者的一种辅助技术。

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

作者信息

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

机构信息

Centre for Psychology, Behaviour and Achievement, Coventry University, Coventry CV1 5FB, UK; Autism Research Centre, Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge CB2 8AH, UK.

Toshiba Research Europe Ltd., 208 Science Park, Cambridge CB4 0GZ, UK.

出版信息

Comput Vis Image Underst. 2016 Jul;148:193-200. doi: 10.1016/j.cviu.2015.08.011.

DOI:10.1016/j.cviu.2015.08.011
PMID:27375348
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4913554/
Abstract

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.

摘要

患有自闭症谱系障碍(ASC)的成年人在识别他人情绪并做出适当反应方面存在显著困难。ASC的临床特征意味着面对面或小组干预可能不适用于这个临床群体。本文探讨了一种新的交互技术——将文本转换为情感丰富的语音——在提高ASC成年人的情绪处理能力和对面部注意力方面的潜力。我们展示了一种生成近乎视频真实感化身(XpressiveTalk)的方法,它可以生成一个面部说出输入文本的视频,且带有多种情感语调。然后我们证明普通成年人能够正确识别XpressiveTalk所描绘的情绪。患有ASC的成年人在从XpressiveTalk推断情绪时的准确性明显低于对照组,但仍高于随机水平。与原始女演员相比,两组在从XpressiveTalk推断悲伤情绪时都明显更准确,并且将这些表情评为明显更受欢迎和更逼真。本文还讨论了XpressiveTalk作为ASC成年人辅助技术的潜在应用。

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