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
v1.0, the initial release, provides 12,523 recordings for 306 participants
collected 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 initial 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.