Training-Free Cross-Lingual Dysarthria Severity Assessment via Phonological Subspace Analysis in Self-Supervised Speech Representations
This paper introduces a training-free, cross-lingual method that quantifies dysarthria severity by measuring the degradation of phonological feature subspaces in frozen self-supervised speech representations using only healthy control data, thereby providing clinically interpretable profiles across multiple languages and etiologies without requiring labeled pathological speech.