Speech technology is not appropriately explored even though modern advances in speech
technology—especially those driven by deep learning (DL) technology—offer …

Developing automatic methods to detect Parkinson's disease (PD) from speech has
attracted increasing interest as these techniques can potentially be used in telemonitoring …

In the light of the current COVID-19 pandemic, the need for remote digital health assessment
tools is greater than ever. This statement is especially pertinent for elderly and vulnerable …

As a common mental disorder, depression becomes a major threat to human health and
may even heavily influence one's daily life. Considering this background, it is necessary to …

Automatic methods for the detection of pathological voice from healthy speech can be
considered as potential clinical tools for medical treatment. This study investigates the …

Depression is a large-scale mental health problem and a challenging area for machine
learning researchers in detection of depression. Datasets such as Distress Analysis …

Preserving a patient's identity is a challenge for automatic, speech-based diagnosis of
mental health disorders. In this paper, we address this issue by proposing adversarial …

In this paper, a data augmentation method is proposed for depression detection from speech
signals. Samples for data augmentation were created by changing the frame-width and the …

While speech-based depression detection methods that use speaker-identity features, such
as speaker embeddings, are popular, they often compromise patient privacy. To address this …

Depression disorder is one of the major causes of disability in the world that can lead to
tragic outcomes. In this paper, we propose a method for using an approximation to a mental …