Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information

The human voice contains complex acoustic markers which have been linked to
important health conditions including dementia, mood disorders, and cancer.
When viewed as a biomarker, voice is a promising characteristic to measure as
it is simple to collect, cost-effective, and has broad clinical utility.
Recent advances in artificial intelligence have provided techniques to extract
previously unknown prognostically useful information from dense data elements
such as images. The Bridge2AI-Voice project seeks to create an ethically
sourced flagship dataset to enable future research in artificial intelligence
and support critical insights into the use of voice as a biomarker of health.
Here we present Bridge2AI-Voice, a comprehensive collection of data derived
from voice recordings with corresponding clinical information.

Bridge2AI-Voice v2.0 contains data for 19,271 recordings collected from 442
participants across five sites in North America. Participants were selected
based on known conditions which manifest within the voice waveform including
voice disorders, neurological disorders, mood disorders, and respiratory
disorders. The release contains data considered low risk, including
derivations such as spectrograms but not the original voice recordings.
Detailed demographic, clinical, and validated questionnaire data are also made
available.

Audio recordings are included on a companion release on PhysioNet with the
title "Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to
health information (Audio Included)". Please see that project for details to
request access.