This paper is the first review into the automatic analysis of speech for use as an objective
predictor of depression and suicidality. Both conditions are major public health concerns; …

Depression has become one of the most common mental illnesses in the world. For better
prediction and diagnosis, methods of automatic depression recognition based on speech …

Abstract Clinical depression or Major Depressive Disorder (MDD) is a common and serious
medical illness. In this paper, a deep Recurrent Neural Network-based framework is …

Depression is a global mental health problem, the worst case of which can lead to suicide.
An automatic depression detection system provides great help in facilitating depression self …

This paper addresses multi-modal depression analysis. We propose a multi-modal fusion
framework composed of deep convolutional neural network (DCNN) and deep neural …

An estimated 350 million people worldwide are affected by depression. Using affective
sensing technology, our long-term goal is to develop an objective multimodal system that …

Abstract Background and Objective: Major Depressive Disorder is a highly prevalent and
disabling mental health condition. Numerous studies explored multimodal fusion systems …

Speech carries essential information about the speaker's physiology and possible
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …

Background Automatic diagnosis of depression based on speech can complement mental
health treatment methods in the future. Previous studies have reported that acoustic …

Depression is a common and serious mood disorder that negatively affects the patient's
capacity of functioning normally in daily tasks. Speech is proven to be a vigorous tool in …