Speech datasets are crucial for training Speech Language Technologies (SLT); however,
the lack of diversity of the underlying training data can lead to serious limitations in building …

Dysarthric speech recognition has posed major challenges due to lack of training data and
heavy mismatch in speaker characteristics. Recent ASR systems have benefited from readily …

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 …

Speakers with dysarthria often struggle to accurately pronounce words and effectively
communicate with others. Automatic speech recognition (ASR) is a powerful tool for …

Purpose Speech disorders profoundly impact the overall quality of life by impeding social
operations and hindering effective communication. This study addresses the gap in …

Automatic recognition of dysarthric speech remains a highly challenging task to date. Neuro-
motor conditions and co-occurring physical disabilities create difficulty in large-scale data …

Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating preventive care and
delay progression. Speech based automatic AD screening systems provide a non-intrusive …

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 …

Automatic speech recognition (ASR) researchers are working to address the differing
transcription performance of ASR by accent or dialect. However, research often has a limited …

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