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 v3.1 contains data for 833 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.