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Linguistic and Acoustic Features for Automatic Identification of Autism Spectrum Disorders in Children's Narrative

机译:自动识别儿童叙事中自闭症谱系障碍的语言和声学特征

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摘要

Autism spectrum disorders are developmental disorders characterised as deficits in social and communication skills, and they affect both verbal and non-verbal communication. Previous works measured differences in children with and without autism spectrum disorders in terms of linguistic and acoustic features, although they do not mention automatic identification using integration of these features. In this paper, we perform an exploratory study of several language and speech features of both single utterances and full narratives. We find that there are characteristic differences between children with autism spectrum disorders and typical development with respect to word categories, prosody, and voice quality, and that these differences can be used in automatic classifiers. We also examine the differences between American and Japanese children and find significant differences with regards to pauses before new turns and linguistic cues.
机译:自闭症谱系障碍是发展性障碍,其特征是社交和沟通技巧不足,并且影响言语和非言语交流。尽管他们没有提到使用这些特征的集成进行自动识别,但以前的著作测量了有自闭症谱系障碍和没有自闭症谱系障碍的儿童的语言和声学特征的差异。在本文中,我们对单个话语和完整叙述的几种语言和语音特征进行了探索性研究。我们发现,自闭症谱系障碍儿童与典型发展之间在单词类别,韵律和语音质量方面存在特征差异,并且这些差异可用于自动分类器。我们还研究了美国和日本儿童之间的差异,发现在新的转弯和语言提示之前的停顿方面存在重大差异。

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  • 会议地点 Baltimore MA(US)
  • 作者单位

    Graduate School of Information Science, Nara Institute of Science and Technology;

    Graduate School of Information Science, Nara Institute of Science and Technology;

    Graduate School of Information Science, Nara Institute of Science and Technology;

    Graduate School of Information Science, Nara Institute of Science and Technology;

    Graduate School of Information Science, Nara Institute of Science and Technology;

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