# healthnexus d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- Name
    Purpose
  Response
    Create an ethically sourced flagship dataset to enable AI research on voice as a biomarker of health by linking derived voice data with demographic, clinical, and validated questionnaire information.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health (NIH) | Bridge2AI: Voice as a Biomarker of Health - Building an ethically sourced, bioacoustic database | 3OT2OD032720-01S1

📊

## Composition

What do the instances represent?

Instances

Counts | Data Type | Instance Type | Name | Representation
--- | --- | --- | --- | ---
12523 | Derived spectrograms (513 x N), acoustic, phonetic, and prosodic features extracted from raw audio; ... | Audio-derived data (per recording) | Voice-derived recordings | Voice-derived recordings (spectrograms/features) linked to metadata
306 | Tabular phenotype data (one row per participant) with data dictionary | Participant-level records | Participants | Participants with linked demographic, clinical, and questionnaire data

Subpopulations

- Name
    Adult cohort
  Identification
    - v1.0 includes adults only across five disease cohorts
  Distribution
    - 306 participants; disease-targeted cohorts (voice, neurological, mood/psychiatric, respiratory)

Distribution Formats

- Name
    Files in v1.0
  Description
    - spectrograms.parquet (derived spectrograms; 513 x N per recording; includes participant_id, session_id, task_name)
    - phenotype.tsv (participant-level demographics, acoustic confounders, validated questionnaires)
    - phenotype.json (data dictionary for phenotype.tsv)
    - static_features.tsv (one row per recording with acoustic/phonetic/prosodic features)
    - static_features.json (data dictionary for static_features.tsv)

Distribution Dates

- Name
    Initial release
  Description
    - 2024-11-27

🔍

## Collection Process

How was the data acquired?

ID *
doi:10.57764/qb6h-em84
Name
Bridge2AI-Voice
Title
Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information v1.0
Description
Bridge2AI-Voice is a comprehensive collection of data derived from voice recordings linked to corresponding clinical information to enable research on voice as a biomarker of health. Version 1.0 provides 12,523 recordings for 306 participants collected across five sites in North America. Participants were selected based on conditions known to manifest in the voice waveform (voice, neurological, mood/psychiatric, and respiratory disorders). This initial release contains low-risk derived data (e.g., spectrograms and extracted features) and detailed demographic/clinical/questionnaire data; raw audio waveforms are not included in v1.0.
Language
en
Page
https://doi.org/10.57764/qb6h-em84
Issued
2024-11-27
Keywords

- voice
- bridge2ai
- audio
- biomarker
- health
- credentialed access

Created By

- Alistair Johnson
- Jean-Christophe Bélisle-Pipon
- David Dorr
- Satrajit Ghosh
- Philip Payne
- Maria Powell
- Anaïs Rameau
- Vardit Ravitsky
- Alexandros Sigaras
- Olivier Elemento
- Yael Bensoussan

Addressing Gaps

- Name
    Gap addressed
  Response
    Addresses the lack of large, diverse, multi-institutional voice datasets linked to health information with standardized collection protocols and ethical oversight; mitigates prior limitations such as small datasets and limited demographic diversity reporting.

Sampling Strategies

1. Name
     Sampling approach
   Is Sample
     - True
   Is Random
     - False
   Source Data
     - Patients presenting at specialty clinics/institutions at five North American sites
   Is Representative
     - False
   Why Not Representative
     - Purposeful selection into five disease cohorts; v1.0 includes adults only
   Strategies
     - Deterministic cohort-based enrollment using inclusion/exclusion screening

Collection Mechanisms

- Name
    Data collection mechanisms
  Description
    - Standardized protocol using a custom tablet application; headset used when possible
    - Clinical/demographic and validated questionnaires collected in-app
    - Data exported and converted from REDCap; processing via open-source b2aiprep library

Data Collectors

- Name
    Data collection personnel
  Description
    - Project investigators at specialty clinics and institutions screened and enrolled participants

Collection Timeframes

- Name
    Collection timeframe
  Description
    - Collected across five sites in North America; specific calendar dates not specified in this record

Ethical Reviews

- Name
    Ethics and IRB/REB review
  Description
    - Approved by the University of South Florida Institutional Review Board
    - Submitted for review to the University of Toronto Research Ethics Board

Preprocessing Strategies

- Name
    Audio preprocessing and feature derivation
  Description
    - Raw audio converted to mono, resampled to 16 kHz with Butterworth anti-aliasing filter
    - Spectrograms via STFT (25 ms window, 10 ms hop, 512-point FFT)
    - Acoustic features via OpenSMILE
    - Phonetic/prosodic features via Parselmouth and Praat (F0, formants, voice quality)
    - Transcriptions generated using OpenAI Whisper Large (free speech transcripts not included in v1.0)
  Used Software

    Name
    OpenSMILE
    Parselmouth
    Praat
    OpenAI Whisper Large
    torchaudio
    b2aiprep

Labeling Strategies

- Name
    Transcription and derived annotations
  Description
    - Automatic transcription using OpenAI Whisper Large for certain tasks; free speech transcripts were removed prior to release
  Used Software
    - Name
        OpenAI Whisper Large

Raw Sources

- Name
    Raw audio availability
  Description
    - Raw audio waveforms were not distributed in v1.0; only derived spectrograms and features are provided. Future releases aim to include audio with additional safeguards.

External Resources

External Resources | Name
--- | ---
https://docs.b2ai-voice.org | Documentation website
https://doi.org/10.5281/zenodo.14148755 | Bridge2AI Voice REDCap (v3.20.0)

Confidential Elements

- Name
    Confidentiality considerations
  Description
    - Contains clinical and questionnaire data linked to participants; v1.0 includes only low-risk derived data and excludes raw audio

Content Warnings
Sensitive Elements

- Name
    Sensitive data elements
  Description
    - Health-related data (demographics, clinical information, validated questionnaires)

Is Deidentified

- Name
    De-identification
  Description
    - HIPAA Safe Harbor identifiers removed (e.g., names, detailed dates, contact identifiers, IDs)
    - State/province removed; country of data collection retained
    - Free speech transcripts removed
    - Raw audio waveforms omitted from this release

Ip Restrictions
Regulatory Restrictions
Maintainers

- Name
    Health Data Nexus
  Description
    - Supported by the Temerty Centre for AI Research and Education in Medicine (Temerty Foundation)

Errata
Is Tabular
Mixed (tabular phenotype/features and array-based parquet spectrograms)
🚀

## Uses

What (other) tasks could the dataset be used for?

Tasks

- Name
    Intended tasks
  Response
    Develop and evaluate AI/ML methods for detecting, characterizing, and monitoring health conditions from voice-derived representations and associated clinical data.

License And Use Terms

Name
  Access, license, and terms
Description
  - License
      Bridge2AI Voice Registered Access License
  - Data Use Agreement
      Bridge2AI Voice Registered Access Agreement
  - Access
      Credentialed users only; must sign DUA
  - Required Training
      TCPS 2: CORE 2022
  - This is a restricted-access resource distributed via Health Data Nexus

📤

## Distribution

How will the dataset be distributed?

DOI
doi:10.57764/qb6h-em84
Version Access

Name
  Versioning and access to latest
Description
  - Latest Version DOI Resolver
      https://doi.org/10.57764/3sg0-7440

🔄

## Maintenance

How will the dataset be maintained?

Version
1.0
Updates

Name
  Update plans
Description
  - Future releases aim to include voice waveforms (raw audio) with additional precautions to ensure data security

Generated on 2025-11-09 10:17:34 using Bridge2AI Data Sheets Schema