5 papers
Autoencoder based optimized SSL representations: Complexity Minimization and improved Dysarthric ASR
Paban Sapkota, Hemant Kumar Kathania, Mikko Kurimo +2
Self-supervised learning (SSL) models extract rich speech representations but often come with high-dimensional features, increasing computational complexity. This work explores an…
DSSCNet: A Transfer Learning Framework for Cross-Corpus Dysarthric Speech Severity Classification
Arnab Kumar Roy, Hemant Kumar Kathania, Paban Sapkota +2
Dysarthric speech severity classification is challenging due to speaker variability, class imbalance, and limited datasets. This study introduces DSSCNet, a deep learning model tha…
Improving End-to-End Speech Recognition for Dysarthric Speech through In-Domain Data Augmentation
Paban Sapkota, Hemant Kumar Kathania, Sudarsana Reddy Kadiri +1
Dysarthric speech recognition is crucial for facilitating effective communication among individuals with dysarthria. However, accurately recognizing dysarthric speech poses signifi…
Systematic Study of Dysarthric Speech Recognition: Spectral Features and Acoustic Models
Paban Sapkota, Hemant Kumar Kathania, Mikko Kurimo +2
The challenge associated with recognizing dysarthric speech primarily arises from pronounced acoustic variability attributed to impaired articulatory precision. Past research has d…
Enhancing Speaker-Independent Dysarthric Speech Severity Classification with DSSCNet and Cross-Corpus Adaptation
Arnab Kumar Roy, Hemant Kumar Kathania, Paban Sapkota
Dysarthric speech severity classification is crucial for objective clinical assessment and progress monitoring in individuals with motor speech disorders. Although prior methods ha…