Dysarthric speech has several pathological characteristics, such as discontinuous
pronunciation, uncontrolled volume, slow speech, explosive pronunciation, improper …

Speakers with dysarthria often struggle to accurately pronounce words and effectively
communicate with others. Automatic speech recognition (ASR) is a powerful tool for …

In recent years, due to the rise in the population and aging, the prevalence of neurological
diseases is also increasing year by year. Among these patients with Parkinson's disease …

Voice prosody measures have been linked with Alzheimer's disease (AD), but it is unclear
whether they are associated with normal cognitive aging. We assessed relationships …

Dysarthric speech recognition requires a learning technique that is able to capture dysarthric
speech specific features. Dysarthric speech is considered as speech with source distortion …

Speech disorders are associated with different degrees of functional and structural
abnormalities. However, the abnormalities associated with specific disorders, and the …

Abstract Machine learning (ML) and Deep Neural Networks (DNN) have greatly aided the
problem of Automatic Speech Recognition (ASR). However, accurate ASR for dysarthric …

Background Speech disorders are common in patients with Multiple Sclerosis (MS). They
can be assessed with several methods, which are however expensive, complex, and not …

Purpose To cross-culturally adapt and validate the Radboud Dysarthria Assessment (RDA)
and the speech component of the Radboud Oral Motor inventory for Parkinson's disease …

Posterior cranial fossa (PCF) tumors in childhood are often associated with ataxia as well as
other motor, neurobehavioral and linguistic impairment. The use of a reliable outcome …