A speech-text cross-attention model improves dysarthria detection and severity classification over speech-only models on the UA-Speech database, but the gain disappears for detection on unseen speakers and words.
Speech-language patholo- gists’ use of intelligibility measures in adults with dysarthria,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.AI 1years
2024 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
A Multi-modal Approach to Dysarthria Detection and Severity Assessment Using Speech and Text Information
A speech-text cross-attention model improves dysarthria detection and severity classification over speech-only models on the UA-Speech database, but the gain disappears for detection on unseen speakers and words.