Automatic recognition of disordered speech remains a highly challenging task to date due to
data scarcity. This paper presents a reinforcement learning (RL) based on-the-fly data …

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 …

Automatic recognition of disordered speech remains a highly challenging task to date. The
underlying neuro-motor conditions, often compounded with co-occurring physical …

Automatic recognition of disordered speech remains a highly challenging task to date. The
underlying neuro-motor conditions, often compounded with co-occurring physical …

Articulatory features are inherently invariant to acoustic signal distortion and have been
successfully incorporated into automatic speech recognition (ASR) systems for normal …

Automatic recognition of disordered and elderly speech remains highly challenging tasks to
date due to data scarcity. Parameter fine-tuning is often used to exploit the large quantities of …

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 …

Automatic recognition of disordered and elderly speech remains a highly challenging task to
date due to the difficulty in collecting such data in large quantities. This paper explores a …

Abstract Machine learning (ML) and Deep Neural Networks (DNN) have greatly aided the
problem of Automatic Speech Recognition (ASR). However, accurate ASR for dysarthric …

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 …