Recently, depression research has received considerable attention and there is an urgent
need for objective and validated methods to detect depression. Depression detection based …

Speech-based automatic depression detection systems have been extensively explored
over the past few years. Typically, each speaker is assigned a single label (Depressive or …

Introduction As a biomarker of depression, speech signal has attracted the interest of many
researchers due to its characteristics of easy collection and non-invasive. However, subjects' …

Depression (major depressive disorder) is one of the most common mental illnesses
worldwide, causing feelings of sadness and loss of interest, and is a leading cause of …

As Natural Language Processing (NLP) systems become increasingly integrated into human
social life, these technologies will need to increasingly rely on social intelligence. Although …

Phonetic data are used in several ways outside of the core field of phonetics. This paper
offers the perspective of one such field, sociophonetics, towards another, the study of …

A significant number of studies apply acoustic and linguistic characteristics of human speech
as prominent markers of dementia and depression. However, studies on discriminating …

Traditional screening practices for anxiety and depression pose an impediment to
monitoring and treating these conditions effectively. However, recent advances in NLP and …

Background While speech analysis holds promise for mental health assessment, research
often focuses on single symptoms, despite symptom co-occurrences and interactions. In …

Depression is the most common psychological disorder and is considered as a leading
cause of disability and suicide worldwide. An automated system capable of detecting signs …