Extraction of Narrative Recall Patterns for Neuropsychological Assessment

Poor narrative memory is associated with a variety of neurodegenerative and developmental disorders, such as autism and Alzheimer’s related dementia. Hence, narrative recall tasks are included in most standard neurological examinations. In this paper, we explore methods for automatically assessing the quality of retellings via alignment to the original narrative. Word alignments serve both to automate manual scoring and to derive other features related to narrative coherence that can be used for diagnostic classification. Despite relatively high word alignment error rates, the automatic alignments provide sufficient information to achieve nearly as accurate diagnostic classification as manual scores. Furthermore, additional features that become available with alignment provide utility in classifying subject groups. While the additional features we explore here did not provide additive gains in accuracy, they point the way to the development of many potentially useful features in this domain.