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 …

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 …

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

This paper presents a novel approach for automated dysarthria detection and severity
assessment using a variable short-time Fourier transform layered convolutional neural …

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

Automatic detection and severity level classification of dysarthria from speech enables non-
invasive and effective diagnosis that helps clinical decisions about medication and therapy …

Dysarthria is a medical condition that impairs an individual's ability to speak clearly due to
muscle weakness or paralysis. To diagnose and monitor dysarthria severity, this article …

Automatic detection and severity level classification of dysarthria directly from acoustic
speech signals can be used as a tool in medical diagnosis. In this work, the pre-trained …

Dysarthria is a motor speech disorder that impacts verbal articulation and co-ordination,
resulting in slow, slurred and imprecise speech. Automated classification of dysarthria …