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

This article proposes a noninvasive computer-aided assessment approach based on
optimized convolutional neural network for healthy and pathological voice detection. Firstly …

In recent years, deep learning methods in automatic pathological voice detection (APVD)
have gained satisfying results. However, most deep learning methods in APVD cannot …

To distinguish pathological voices from healthy voices, automatic voice pathology detection
systems can be built using machine learning (ML) and deep learning (DL) techniques. To …

In clinical settings, early diagnosis and objective assessment depend on the detection of
voice pathology. To classify anomalous voices, this work uses an approach that combines …

In recent years, voice pathology detection (VPD) has received considerable attention
because of the increasing risk of voice problems. Several methods, such as support vector …

Miniature on-chip sources based on the collapsing field domain phenomenon in GaAs have
advanced compact sub-picosecond time-domain imaging schemes operating in the 100 …

Machine learning (ML) has shown promising results in the field of voice disorder detection
over the past decade. However, the diversity of recording conditions, audio content …

Automatic speech quality assessment has raised more attention as an alternative or support
to traditional perceptual clinical evaluation. However, most research so far only gains good …