# healthnexus tab metadata d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- Name
    Purpose
  Response
    Create an ethically sourced, diverse, multi-institutional voice dataset linked to health information to enable future AI research and insights into voice as a biomarker of health.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health (NIH) | Bridge2AI: Voice as a Biomarker of Health - Building an ethically sourced, bioacoustic database to understand disease like never before | 3OT2OD032720-01S1

📊

## Composition

What do the instances represent?

Instances

1. Name
     Instance structure
   Representation
     Voice recordings linked to clinical and questionnaire information
   Instance Type
     Participants, recording sessions, and derived per-recording data
   Data Type
     Derived data only: STFT spectrograms, acoustic/phonetic/prosodic features, and (non-free-speech) transcriptions; tabular phenotype data per participant.
   Counts
     12,523
   Label
     Dataset includes cohort membership and clinical/questionnaire variables; no explicit task labels provided in this release.
   Sampling Strategies
     1. Name
          Sampling
        Is Sample
          - True
        Is Random
          - False
        Source Data
          - Patients at specialty clinics across five sites in North America
        Is Representative
          - False
        Why Not Representative
          - Targeted enrollment of disease cohorts with known voice manifestations
        Strategies
          - Purposive/clinical cohort-based sampling
   Missing Information

Subpopulations

- Name
    Disease cohorts
  Identification
    - Voice disorders
    - Neurological and neurodegenerative disorders
    - Mood and psychiatric disorders
    - Respiratory disorders
  Distribution
    - Adult cohort only in v1.0; detailed cohort counts not provided.

Distribution Formats

- Name
    Release files
  Description
    - spectrograms.parquet (derived spectrogram data)
    - static_features.tsv and static_features.json (per-recording features and data dictionary)
    - phenotype.tsv and phenotype.json (per-participant phenotype data and data dictionary)

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
Description
Bridge2AI-Voice v1.0 is a restricted-access dataset enabling research into voice as a biomarker of health. The initial release provides 12,523 recordings for 306 adult participants collected across five sites in North America, with accompanying demographic, clinical, and validated questionnaire data. To reduce re-identification risk, only derived data are released (e.g., spectrograms and extracted acoustic/phonetic features); original audio waveforms and free-speech transcripts are not included. Participants were selected from cohorts with conditions known to manifest in voice (voice disorders, neurological and neurodegenerative disorders, mood and psychiatric disorders, and respiratory disorders). Standardized collection protocols were used; raw audio was converted to mono, resampled to 16 kHz with a Butterworth anti-aliasing filter, and used to compute STFT spectrograms and features (openSMILE, Praat/Parselmouth, torchaudio). Transcriptions were generated using Whisper Large but free speech transcripts were removed for release.
Language
en
Page
https://doi.org/10.57764/qb6h-em84
Issued
2024-11-27
Keywords

- voice
- bridge2ai
- audio

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
    Addressing gap
  Response
    Addresses the lack of large, high-quality, diverse, standardized, multi-institutional voice datasets linked to health biomarkers suitable for AI research.

Creators

- Name
    Bridge2AI-Voice Team

Subsets

- Name
    Adult cohort v1.0
  Is Data Split
    no
  Is Subpopulation
    Adult cohort only in v1.0

Relationships

- Name
    Participant-session-recording linkage
  Description
    - Participants may have multiple sessions; sessions include multiple recordings/tasks.

Splits
Anomalies
External Resources

1. Name
     Documentation
   External Resources
     - https://docs.b2ai-voice.org
   Future Guarantees
     - Not stated
   Archival
     - DOI-registered dataset landing page at Health Data Nexus
   Restrictions
     - Credentialed access with required training and DUA

Confidential Elements

- Name
    Confidentiality
  Description
    - Clinical and demographic data are included; identifiers removed per HIPAA Safe Harbor.

Content Warnings
Is Deidentified

Name
  De-identification
Description
  - HIPAA Safe Harbor identifiers removed (e.g., names, detailed dates, contact and device identifiers).
  - State/province removed; country of data collection retained.
  - Free speech transcripts removed.
  - Original audio waveforms omitted from v1.0; only derived data released.

Sensitive Elements

- Name
    Sensitive data
  Description
    - Contains health-related and demographic information.

Acquisition Methods

1. Name
     Data acquisition
   Description
     - Standardized protocol with voice tasks (e.g., sustained vowel), clinical and targeted questionnaires.
     - Participants enrolled from specialty clinics into predefined cohorts.
   Was Directly Observed
     yes (voice recordings)
   Was Reported By Subjects
     yes (questionnaires)
   Was Inferred Derived
     yes (features and spectrograms derived from raw audio)
   Was Validated Verified
     Standardized acquisition protocols were used; preprocessing and feature extraction applied consistently.

Collection Mechanisms

- Name
    Collection mechanisms
  Description
    - Custom tablet application; headset used for data collection when possible.
    - Data exported and converted from REDCap using an open-source library.

Data Collectors

- Name
    Data collectors
  Description
    - Project investigators at five North American sites; participant screening against inclusion/exclusion criteria.

Ethical Reviews

- Name
    Ethics and IRB/REB review
  Description
    - Data collection and sharing 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 extraction
  Description
    - Mono conversion; resampled to 16 kHz with a Butterworth anti-aliasing filter.
    - STFT spectrograms using 25 ms window, 10 ms hop, 512-point FFT.
    - Acoustic features via openSMILE.
    - Phonetic/prosodic measures via Parselmouth and Praat.
    - Derived audio features via torchaudio.
  Used Software

    Name | URL
    --- | ---
    b2aiprep | https://github.com/sensein/b2aiprep
    openSMILE |
    Praat |
    Parselmouth |
    torchaudio |

Labeling Strategies

- Name
    Transcription
  Description
    - Transcriptions generated using OpenAI Whisper Large; free speech transcripts removed from release.

Cleaning Strategies

- Name
    De-identification and release filtering
  Description
    - Removal of HIPAA Safe Harbor identifiers.
    - Removal of state/province; retention of country only.
    - Exclusion of free speech transcripts and original audio waveforms from v1.0.

Raw Sources

- Name
    Raw audio
  Description
    - Collected but not released in v1.0; derived spectrograms and features provided instead.

Maintainers

- Name
    Hosting and support
  Description
    - Health Data Nexus; Temerty Centre for AI Research and Education in Medicine (supported by the Temerty Foundation).

🚀

## Uses

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

Tasks

- Name
    Intended tasks
  Response
    Development and evaluation of AI methods for health-related voice analytics using derived spectrograms and acoustic/phonetic features; exploration of associations between voice signals and clinical/demographic factors.

License And Use Terms

Name
  License and access terms
Description
  - License
      Bridge2AI Voice Registered Access License.
  - Access Policy
      Only credentialed users who sign the DUA can access the files.
  - Data Use Agreement
      Bridge2AI Voice Registered Access Agreement.
  - Required Training
      TCPS 2: CORE 2022.

📤

## Distribution

How will the dataset be distributed?

DOI
doi:10.57764/qb6h-em84
Version Access

Name
  Versioning and access
Description
  - Latest Version DOI
      https://doi.org/10.57764/3sg0-7440
  - This record describes version 1.0 (doi:10.57764/qb6h-em84).

🔄

## Maintenance

How will the dataset be maintained?

Version
1.0
Updates

Name
  Update plan
Description
  - Future releases aim to include voice waveforms with additional data security precautions.

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