The growing and aging of the world population have driven the shortage of medical
resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid …

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 common and debilitating symptom of many neurodegenerative diseases,
including those resulting in ataxia. Changes to speech lead to significant reductions in …

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

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

Training machine learning algorithms for speech applications requires large, labeled
training data sets. This is problematic for clinical applications where obtaining such data is …

Dysarthria is a motor speech impairment, often characterized by slow and slurred speech
that is generally incomprehensible by human listeners. An understanding of the intelligibility …

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 …