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COMPUTATIONAL ANALYSIS OF TRAJECTORIES OF LINGUISTIC DEVELOPMENT IN AUTISM

机译:自闭症语言发展轨迹的计算分析

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摘要

Deficits in semantic and pragmatic expression are among the hallmark linguistic features of autism. Recent work in deriving computational correlates of clinical spoken language measures has demonstrated the utility of automated linguistic analysis for characterizing the language of children with autism. Most of this research, however, has focused either on young children still acquiring language or on small populations covering a wide age range. In this paper, we extract numerous linguistic features from narratives produced by two groups of children with and without autism from two narrow age ranges. We find that although many differences between diagnostic groups remain constant with age, certain pragmatic measures, particularly the ability to remain on topic and avoid digressions, seem to improve. These results confirm findings reported in the psychology literature while underscoring the need for careful consideration of the age range of the population under investigation when performing clinically oriented computational analysis of spoken language.
机译:语义和语用表达上的缺陷是自闭症的标志性语言特征。在得出临床口语测量值的计算相关性方面的最新工作表明,自动语言分析可用于表征自闭症儿童的语言。但是,这项研究大部分都集中在仍在学习语言的幼儿或覆盖广泛年龄段的少数人群上。在本文中,我们从两个狭窄年龄段的两组有自闭症和无自闭症的儿童的叙述中提取了众多语言特征。我们发现,尽管诊断组之间的许多差异随着年龄的增长而保持不变,但某些实用的措施,尤其是保持话题性和避免离题的能力似乎有所改善。这些结果证实了心理学文献中报告的发现,同时强调了在进行面向临床的口头计算分析时,需要仔细考虑被调查人群的年龄范围。

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