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 …

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

Dysarthria, a speech disorder stemming from neurological conditions, affects communication
and life quality. Precise classification and severity assessment are pivotal for therapy but are …

Automatic methods for the detection of pathological voice from healthy speech can be
considered as potential clinical tools for medical treatment. This study investigates the …

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 …

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 neurological speech disorder that can significantly impact affected
individuals' communication abilities and overall quality of life. The accurate and objective …

Recently, spectro-temporal representation of speech has been used in many fields of
speech processing. Owing to this, we explore the use of spectro-temporal representation for …

In clinical practice, assessment of intelligibility in speakers with dysarthria is performed by
speech-language pathologists through auditory perceptual tests which demand patients' …