A review of depression and suicide risk assessment using speech analysis
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; …
predictor of depression and suicidality. Both conditions are major public health concerns; …
Automatic depression recognition by intelligent speech signal processing: A systematic survey
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 …
prediction and diagnosis, methods of automatic depression recognition based on speech …
A multi-modal open dataset for mental-disorder analysis
According to the WHO, the number of mental disorder patients, especially depression
patients, has overgrown and become a leading contributor to the global burden of disease …
patients, has overgrown and become a leading contributor to the global burden of disease …
[HTML][HTML] A hybrid model for depression detection using deep learning
Millions of people are suffering from mental illness due to unavailability of early treatment
and services for depression detection. It is the major reason for anxiety disorder, bipolar …
and services for depression detection. It is the major reason for anxiety disorder, bipolar …
[HTML][HTML] Bio-acoustic features of depression: A review
SA Almaghrabi, SR Clark, M Baumert - Biomedical Signal Processing and …, 2023 - Elsevier
Speech carries essential information about the speaker's physiology and possible
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …
pathophysiological conditions. Bio-acoustic voice qualities show promising value for …
Deep learning-based classification of posttraumatic stress disorder and depression following trauma utilizing visual and auditory markers of arousal and mood
BackgroundVisual and auditory signs of patient functioning have long been used for clinical
diagnosis, treatment selection, and prognosis. Direct measurement and quantification of …
diagnosis, treatment selection, and prognosis. Direct measurement and quantification of …
Detecting depression using an ensemble logistic regression model based on multiple speech features
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 …
diagnostic methods are still limited. This study investigated automatic depressed speech …
Investigation of different speech types and emotions for detecting depression using different classifiers
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 …
for reducing the burden of the disease, but current methods of diagnosis remain limited …
Analysis of acoustic space variability in speech affected by depression
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 …
with a speaker's level of clinical depression. This has resulted in spectral and energy based …
Towards automatic depression detection: A BiLSTM/1D CNN-based model
Featured Application The proposed automatic depression detection method aims at:(1)
supporting clinical diagnosis with objective and quantitative measurements and (2) …
supporting clinical diagnosis with objective and quantitative measurements and (2) …