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

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

Abstract Automatic Speech Recognition technology (ASR) has recently witnessed a
paradigm shift with respect to performance accuracy. Nevertheless, impaired speech …

Despite the rapid progress of automatic speech recognition (ASR) technologies targeting
normal speech in recent decades, accurate recognition of dysarthric and elderly speech …

Dysarthric speech recognition helps speakers with dysarthria to enjoy better communication.
However, collecting dysarthric speech is difficult. The machine learning models cannot be …

Automatic recognition of disordered speech remains a highly challenging task to date.
Sources of variability commonly found in normal speech including accent, age or gender …

Dysarthria is a motor speech disorder, resulting in mumbled, slurred or slow speech that is
generally difficult to understand by both humans and machines. Traditional Automatic …

Epidemiological studies suggest that bipolar disorder has a prevalence of about 1% in
European countries, becoming one of the most disabling illnesses in working age adults …

In this paper, we introduce a new corpus of oral cancer speech and present our study on the
automatic recognition and analysis of oral cancer speech. A two-hour English oral cancer …

A key challenge in dysarthric speech recognition is the speaker-level diversity attributed to
both speaker-identity associated factors such as gender, and speech impairment severity …