Speaker-Independent Dysarthria Severity Classification using Self-Supervised Transformers and Multi-Task Learning

arXiv:2403.00854v1 Announce Type: cross
Abstract: Dysarthria, a condition resulting from impaired control of the speech muscles due to neurological disorders, significantly impacts the communication and quality of life of patients. The condition's complexity, human scoring and varied presentations make its assessment and management challenging. This study presents a transformer-based framework for automatically assessing dysarthria severity from raw speech data. It can offer an objective, repeatable, accessible, standardised and cost-effective and compared to traditional methods requiring human expert assessors. We develop …

abstract arxiv assessment classification communication complexity control cs.ai cs.cl cs.lg cs.sd eess.as framework human impacts independent life management multi-task learning patients presentations q-bio.nc quality scoring speaker speech study transformer transformers type