Speech classifiers of paralinguistic traits traditionally learn from diverse hand-crafted low-
level features, by selecting the relevant information for the task at hand. We explore an …

Dysarthria is a motor speech disorder that impacts verbal articulation and co-ordination,
resulting in slow, slurred and imprecise speech. Automated classification of dysarthria …

Dysarthria is a neuro-motor speech disorder that renders speech unintelligible, in
proportional to its severity. Assessing the severity level of dysarthria, apart from being a …

Assessing the severity level of dysarthria can provide an insight into the patient's
improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech …

Speech is a complex process that can break in many different ways and lead to a variety of
voice disorders. Dysarthria is a voice disorder where individuals are unable to control one or …

Although the UA-Speech and TORGO databases of control and dysarthric speech are
invaluable resources made available to the research community with the objective of …

In the past, the performance of machine learning algorithms depended heavily on the
representation of the data. Well-designed features therefore played a key role in speech and …

In this work, we investigate the joint use of articulatory and acoustic features for automatic
speech recognition (ASR) of pathological speech. Despite long-lasting efforts to build …

Automatic detection and severity level classification of dysarthria from speech enables non-
invasive and effective diagnosis that helps clinical decisions about medication and therapy …

Despite significant advancements in automatic speech recognition (ASR) technology, even
the best performing ASR systems are inadequate for speakers with impaired speech. This …