Alignment of spoken narratives for automated neuropsychological assessment

Narrative recall tasks are commonly included in neurological examinations, as deficits in narrative memory are associated with disorders such as Alzheimer's dementia. We explore methods for automatically scoring narrative retellings via alignment to a source narrative. Standard alignment methods, designed for large bilingual corpora for machine translation, yield high alignment error rates (AER) on our small monolingual corpora. We present modifications to these methods that obtain a decrease in AER, an increase in scoring accuracy, and diagnostic classification performance comparable to that of manual methods, thus demonstrating the utility of these techniques for this task and other tasks relying on monolingual alignments.