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 …

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

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 …

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 …

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 …

The automatic speech recognition (ASR) system is increasingly being applied as assistive
technology in the speech impaired community, for individuals with physical disabilities such …

Dysarthria is a speech disorder caused by improper coordination between the brain and the
muscles that produce intelligible speech. Accurately diagnosing the severity of dysarthria is …

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

Background The voice is a prominent tool allowing people to communicate and to change
information in their daily activities. However, any slight alteration in the voice production …