Background: Loneliness has drawn increasing attention over the past few decades due to
rising recognition of its close connection with serious health issues, like dementia. Yet …

Depression detection from speech continues to attract significant research attention but
remains a major challenge, particularly when the speech is acquired from diverse …

Mood disorders present on-going challenges to the medical field, with difficulties ranging
from establishing effective treatments to understanding complexities of one's mood. One …

Generative models, such as Variational Autoen-coders, are being increasingly utilized for
various acoustic modeling tasks, such as anomaly detection from audio signals. Motivated …

In this work, we aim to explore and develop a speech analysis system that identifies
relapses in patients with psychotic disorders (ie, bipolar disorder and schizophrenia) with …

Widespread speech technologies may change the dynamics of mental health (MH)
diagnosis, monitoring, and care by tracking spectrotemporal patterns of speech in a …

Detecting depression from the voice in naturalistic environments is challenging, particularly
for short-duration audio recordings. This enhances the need to interpret and make optimal …

Lexical analysis is a tool designed to assess speech content using a variety of categorical
labels and has been used throughout the schizophrenia spectrum to quantify emotional …

Technological solutions to screen for depression are being researched to combat the rise of
mental health problems in post-secondary students. Specifically, machine learning models …

Bipolar disorder is a chronic mental illness, affecting 4% of Americans, that is characterized
by periodic mood changes ranging from severe depression to extreme compulsive highs …