Recently, we have witnessed Deep Learning methodologies gaining significant attention for
severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its …

Dysarthria is a neuro-motor speech disorder that renders speech unintelligible, in
proportional to its severity. Assessing the severity level of dysarthria, apart from being a …

Dysarthria is a disorder that affects an individual's speech intelligibility due to the paralysis of
muscles and organs involved in the articulation process. As the condition is often associated …

Assessing the severity level of dysarthria can provide an insight into the patient's
improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech …

Dysarthria is a motor speech disability caused by weak muscles and organs involved in the
articulation process, thereby affecting the speech intelligibility of individuals. Because this …

Automated dysarthria severity identification can aid clinicians in monitoring the patient's
progress, and can improve the performance of dysarthric speech recognition systems. In this …

Improving the accuracy of dysarthric speech recognition is a challenging research field due
to the high inter-and intra-speaker variability in disordered speech. In this work, we propose …

Improved performance in speech applications using deep neural networks (DNNs) has
come at the expense of reduced model interpretability. For consumer applications this is not …

Identifying the severity of dysarthria is considered a diagnostic step in monitoring the
patient's progress and a beneficial step in the transcription of dysarthric speech. In this …

Improving the accuracy of personalised speech recognition for speakers with dysarthria is a
challenging research field. In this paper, we explore an approach that non-linearly modifies …