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

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

The success of automatic speech recognition (ASR) benefits a great number of healthy
people, but not people with disorders. The speech disordered may truly need support from …

Despite the rapid progress of automatic speech recognition (ASR) technologies targeting
normal speech, accurate recognition of dysarthric and elderly speech remains a highly …

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

Dysarthric speech recognition is a challenging task due to acoustic variability and limited
amount of available data. Diverse conditions of dysarthric speakers account for the acoustic …

Automatic recognition of elderly and disordered speech remains a highly challenging task to
date. Such data is not only difficult to collect in large quantities, but also exhibits a significant …

Recent studies have reported the success of multi-scale convolution neural network
(MSConvNet) model for many classification applications due to its powerful ability of …

Self-supervised learning (SSL) based speech foundation models have been applied to a
wide range of ASR tasks. However, their application to dysarthric and elderly speech via …

As an essential technology in human–computer interactions, automatic speech recognition
(ASR) ensures a convenient life for healthy people; however, people with speech disorders …