We present a study about automated discourse analysis of oral narrative language in adolescents with autistic spectrum disorder (ASD). The basis of this evaluation is an existing dataset of fictional narrations of individuals with ASD and two matched comparison groups. We use three robust measures for quantifying different aspects of text cohesion on this corpus. These measures and several combinations of them correlate strongly with human cohesion annotations. Our evaluation will show which of these also distinguish the ASD group from the two comparison groups, which do not, and which differences are related to language competence rather than to factors specific to ASD.
Download Full PDF Version (Non-Commercial Use)