Artificial Intelligence #speech recognition#dysarthric speech
Dysarthric Speech Recognition Improved by 4.65% with F-TDNN Model and Pitch Features
A systematic study by researchers from multiple institutions investigates dysarthric speech recognition using spectral features and acoustic models. The study, published on arXiv, demonstrates that incorporating pitch features and using the Factorized Time Delay Neural Network (F-TDNN) model yields a 4.65% relative improvement in isolated word recognition and a 4.63% relative improvement in sentence recognition for dysarthric speech, compared to previous research.
Jun 20, 2026 1 source