Bridge2AI-Voice Pediatric Dataset

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 Pediatric Dataset v3.0 contains derived audio features for
22,620 recordings collected from 300 participants aged 2-18. 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.