AudVowelConsNet: A phoneme-level based deep CNN architecture for clinical depression diagnosis
M Muzammel, H Salam, Y Hoffmann… - Machine Learning with …, 2020 - Elsevier
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 …
capacity of functioning normally in daily tasks. Speech is proven to be a vigorous tool in …
Manifestation of depression in speech overlaps with characteristics used to represent and recognize speaker identity
SH Dumpala, K Dikaios, S Rodriguez, R Langley… - Scientific Reports, 2023 - nature.com
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 …
speech is also starting to be used to detect medical conditions, such as depression. It is not …
Enhanced depression detection from speech using quantum whale optimization algorithm for feature selection
There is an urgent need to detect depression using a non-intrusive approach that is reliable
and accurate. In this paper, a simple and efficient unimodal depression detection approach …
and accurate. In this paper, a simple and efficient unimodal depression detection approach …
Gender bias in depression detection using audio features
A Bailey, MD Plumbley - 2021 29th European Signal …, 2021 - ieeexplore.ieee.org
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 …
learning researchers in detection of depression. Datasets such as Distress Analysis …
A weakly supervised learning framework for detecting social anxiety and depression
Although social anxiety and depression are common, they are often underdiagnosed and
undertreated, in part due to difficulties identifying and accessing individuals in need of …
undertreated, in part due to difficulties identifying and accessing individuals in need of …
Automated screening for distress: A perspective for the future
Distress is a complex condition, which affects a significant percentage of cancer patients and
may lead to depression, anxiety, sadness, suicide and other forms of psychological …
may lead to depression, anxiety, sadness, suicide and other forms of psychological …
[HTML][HTML] Depression screening from voice samples of patients affected by parkinson's disease
Y Ozkanca, M Göksu Öztürk, MN Ekmekci… - Digital …, 2019 - karger.com
Depression is a common mental health problem leading to significant disability worldwide. It
is not only common but also commonly co-occurs with other mental and neurological …
is not only common but also commonly co-occurs with other mental and neurological …
[HTML][HTML] Speech depression recognition based on attentional residual network
X Lu, D Shi, Y Liu, J Yuan - Frontiers in Bioscience-Landmark, 2021 - imrpress.com
Background: Depressive disorder is a common affective disorder, also known as
depression, which is characterized by sadness, loss of interest, feelings of guilt or low self …
depression, which is characterized by sadness, loss of interest, feelings of guilt or low self …
An online attachment style Recognition System based on Voice and Machine Learning
L Gómez-Zaragozá, J Marín-Morales… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Attachment styles are known to have significant associations with mental and physical
health. Specifically, insecure attachment leads individuals to higher risk of suffering from …
health. Specifically, insecure attachment leads individuals to higher risk of suffering from …
Speech based depression severity level classification using a multi-stage dilated cnn-lstm model
N Seneviratne, C Espy-Wilson - arXiv preprint arXiv:2104.04195, 2021 - arxiv.org
Speech based depression classification has gained immense popularity over the recent
years. However, most of the classification studies have focused on binary classification to …
years. However, most of the classification studies have focused on binary classification to …