Objective There are many barriers to accessing mental health assessments including cost
and stigma. Even when individuals receive professional care, assessments are intermittent …

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; …

In this paper, we show that convolutional neural networks can be directly applied to temporal
low-level acoustic features to identify emotionally salient regions without the need for …

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

Early intervention for depression is very important to ease the disease burden, but current
diagnostic methods are still limited. This study investigated automatic depressed speech …

Depression is one of the most common mental disorders. Early intervention is very important
for reducing the burden of the disease, but current methods of diagnosis remain limited …

The sound of a person's voice is commonly used to identify the speaker. The sound of
speech is also starting to be used to detect medical conditions, such as depression. It is not …

The spectral and energy properties of speech have consistently been observed to change
with a speaker's level of clinical depression. This has resulted in spectral and energy based …

Purpose Diagnosis and treatment in psychiatry are still highly dependent on reports from
patients and on clinician judgment. This fact makes them prone to memory and subjectivity …

Reliable, valid, and efficient assessment of depression is critical to identify individuals in
need of treatment and to gauge treatment response. Current methods of assessment are …