Despite the rapid progress of automatic speech recognition (ASR) technologies in the past
few decades, recognition of disordered speech remains a highly challenging task to date …

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

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 …

Raw waveform acoustic modelling has recently received increasing attention. Compared
with the task-blind hand-crafted features which may discard useful information …

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

Building automatic speech recognition (ASR) systems for speakers with dysarthria is a very
challenging task. Although multi-modal ASR has received increasing attention recently …

Audio-visual speech recognition (AVSR) technologies have been successfully applied to a
wide range of tasks. When developing AVSR systems for disordered speech characterized …

There has been a long term interest in using visual information to improve automatic speech
recognition (ASR) system performance. Both audio and visual information are required in …

Automatic speech recognition (ASR) for disordered speech is a challenging task. People
with speech disorders such as dysarthria often have physical disabilities, leading to severe …

Over the last decade, there has been a notable increase in the pervasiveness of
neurological diseases due to population growth and aging. Among individuals with …