Work

Automatic detection of pragmatic deficits in children with autism.

Year: 2012

Type: conference-paper

Abstract: Autism spectrum disorder (ASD) is characterized by atypical and idiosyncratic language, which often has its roots in pragmatic deficits. Identifying and measuring pragmatic language ability is challenging and requires substantial clinical expertise. In this paper, we present a method for automatically identifying pragmatically inappropriate language in narratives using two features related to relevance and topicality. These features, which are derived using techniques from machine translation and information retrieval, are able to distinguish the narratives from children with ASD from those of their language-matched peers and may prove useful in the development of automated screening tools for autism and neurodevelopmental disorders.

Source: PubMed

Authors: Emily Prud'hommeaux, Masoud Rouhizadeh

Institution: Oregon Health & Science University

Language: English

Topic: Autism Spectrum Disorder Research

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funder: National Institute on Deafness and Other Communication Disorders

Award: Automated measurement of language outcomes for neurodevelopmental disorders