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

机译:语言和声学特征,用于自动识别儿童叙事中的自动谱紊乱

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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障碍,其特征在于社会和沟通技能的缺陷,它们都会影响口头和非口头沟通。以前的作品在语言和声学特征方面,在语言和声学特征方面测量了有和没有自闭症频谱障碍的儿童的差异,尽管他们没有使用这些功能的集成而提及自动识别。在本文中,我们对单一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。我们发现自闭症频谱障碍的儿童与典型发展相对于单词类别,韵律和语音质量的典型发展,以及这些差异可以在自动分类器中使用。我们还研究了美国和日本儿童之间的差异,并在新的转弯和语言线索之前发现了对暂停的显着差异。

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