Voice and Language Biomarkers for Mental Health

Overall Aim: To detect mental health symptoms from voice and language data

Team Members: Daniel Low, Debbie Burdinski, Satra Ghosh

Systematic review of studies detecting psychiatric disorders from speech

127 studies, 8 psychiatric disorders, description of acoustic features, guidelines for data acquisition and machine learning models

Link to publication

Collaborators: Kate Bentley

Discovering concerns and changes during COVID-19 on Reddit support groups

Analyzing 800 000+ posts from 2018 to 2021, we tracked changes in semantic content across 15 mental health support groups (e.g., r/SuicideWatch, r/BipolarReddit) and found vulnerable groups and a doubling of posts within a suicidality and loneliness clusters.

Link to publication

Featured in MIT News and CNET

Mental Health Reddit Dataset
Zenodo Github & OSF

Collaborators: Laurie Rumker, Tanya Talkar, John Torous, Guillermo Cecchi

Estimating the effect of peer responses to suicidal posts among veterans

Collaborators: Matt Nock, Walter Dempsey, Kelly Zuromski, Daniel Kessler, RallyPoint

Tracking longitudinal changes in voice and language using ecological momentary assessments

Collaborators: Kate Bentley, Joe Maimone, Daniel Coppersmith, Rebecca Fortrang, Alex Millner, Matt Nock

Tracking changes in speech during transcranial magnetic stimulation trials

Collaborators: Joan Camprodon