4 accepted papers
Caregiver strategy classification in pediatric rehabilitation contexts is strongly motivated by real-world clinical constraints but highly under-resourced and seldom studied in natural language processing settings. We introduce a large dataset of 4,037 caregiver strategies in this setting, a five-fo…
Spoken language presents a compelling medium for non-invasive Alzheimer’s disease (AD) screening, and prior work has examined the use of fine-tuned pretrained language models (PLMs) for this purpose. However, PLMs are often optimized on tasks that are inconsistent with AD classification. Spoken lang…
Identifying early markers of Alzheimer’s disease (AD) trajectory enables intervention in early disease stages when our currently-available interventions are most likely to be beneficial. Research has shown that alterations in speech, as well as linguistic and semantic deviations in spontaneous conve…
Health-related speech datasets are often small and varied in focus. This makes it difficult to leverage them to effectively support healthcare goals. Robust transfer of linguistic features across different datasets orbiting the same goal carries potential to address this concern. To test this hypoth…