Speech processing plays a crucial role in many signal processing applications, while the
last decade has bought gigantic evolution based on machine learning prototype. Speech …

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 …

ABSTRACT ALS is a fatal neurodegenerative disease with no cure. Experts typically
measure disease progression via the ALSFRS-R score, which includes measurements of …

Dysarthric speech recognition is a highly challenging task. The articulatory motor control
problems associated with neuromotor conditions produce large mismatch against normal …

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

Dysarthria is a neuro-motor disorder resulting from the disruption of normal activity in speech
production leading to slow, slurred and imprecise (low intelligible) speech. Automatic …

This paper proposes a new dysarthric speech classification method from coded telephone
speech using glottal features. The proposed method utilizes glottal features, which are …

This paper proposes a new speech feature representation that improves the intelligibility
assessment of dysarthric speech. The formulation of the feature set is motivated from the …

Many acoustic features and machine learning models have been studied to build automatic
detection systems to distinguish dysarthric speech from healthy speech. These systems can …