# healthnexus tab abstract d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- Name
    Primary purpose
  Used Software
  Attributes
    Response
      Create an ethically sourced flagship dataset to enable AI research on voice as a biomarker of health and support clinically meaningful insights.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
- | - | -

📊

## Composition

What do the instances represent?

Instances

- Name
    Recording-level instances
  Used Software
  Attributes
    Representation
      Voice recordings (derived representations) linked to participant clinical and questionnaire data
    Instance Type
      Participants and their associated recording sessions/tasks
    Data Type
      Derived spectrograms (513×N), acoustic features, phonetic and prosodic features, and metadata (demographics, questionnaires). Original audio waveforms excluded in v1.0.
    Counts
      12,523
    Label
      Cohort membership and clinical variables available; no explicit single target label across all instances.
    Sampling Strategies
    Missing Information

Subpopulations

- Name
    Adult cohort and disease categories
  Used Software
  Attributes
    Identification
      - Adult participants only in v1.0
      - Disease Cohorts
          Voice disorders; Neurological and neurodegenerative disorders; Mood and psychiatric disorders; Respiratory disorders
    Distribution
      - 306 adult participants across five sites (detailed distribution not provided)

Distribution Formats

- Name
    File formats
  Used Software
  Attributes
    Description
      - Parquet (.parquet)
      - Tab-separated values (.tsv)
      - JSON (.json)

Distribution Dates

- Name
    Release date
  Used Software
  Attributes
    Description
      - 2024-11-27 (v1.0)

🔍

## Collection Process

How was the data acquired?

ID *
bridge2ai-voice-v1-0
Name
Bridge2AI-Voice
Title
Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information
Description
Bridge2AI-Voice is a comprehensive, ethically sourced dataset for voice as a biomarker of health. Version 1.0 provides 12,523 recordings for 306 adult participants collected across five North American sites, with corresponding demographic, clinical, and validated questionnaire information. Participants were selected from cohorts with conditions known to manifest in the voice (voice disorders, neurological disorders, mood/psychiatric disorders, respiratory disorders; pediatric cohort planned for future releases). In v1.0, low-risk derived data (e.g., spectrograms, acoustic, phonetic, and prosodic features) are released; original audio waveforms are not included. Data are de-identified under HIPAA Safe Harbor (with additional removals such as state/province and free-speech transcripts). Documentation: https://docs.b2ai-voice.org
Language
English
Issued
2024-11-27
Page
https://doi.org/10.57764/qb6h-em84
Keywords

- voice
- bridge2ai
- audio
- biomarker
- health
- spectrograms
- parquet
- tsv
- json

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
  Used Software
  Attributes
    Response
      Lack of large, diverse, multi-institutional, ethically sourced voice datasets linked to clinical information for AI research.

Sampling Strategies

- Name
    Cohort-based clinical sampling
  Used Software
  Attributes
    Is Sample
      - True
    Is Random
      - False
    Source Data
      - Patients presenting at specialty clinics across five North American sites
    Is Representative
      - Not designed to be population-representative
    Representative Verification
    Why Not Representative
      - Purposeful enrollment based on predefined disease cohorts
    Strategies
      - Purposeful cohort-based sampling aligned to predefined conditions

Relationships
Splits
Anomalies
External Resources

- Name
    Documentation and related resources
  Used Software
  Attributes
    External Resources
      - https://docs.b2ai-voice.org
      - doi:10.5281/zenodo.14148755
    Future Guarantees
      - Versioned DOIs provided (latest version DOI available)
    Archival
      - Versioned DOI records (v1.0 and latest-version DOI)
    Restrictions
      - Registered/credentialed access under DUA and training requirements

Confidential Elements

- Name
    Clinical information
  Used Software
  Attributes
    Description
      - Contains clinical/demographic/questionnaire data considered low risk, distributed under registered access and DUA

Content Warnings
Is Deidentified

Name
  De-identification
Used Software
Attributes
  Description
    - HIPAA Safe Harbor identifiers removed
    - State and province removed; country retained
    - Free-speech transcripts removed
    - Audio waveforms omitted in v1.0; only derived/low-risk data released

Sensitive Elements

- Name
    Health-related and biometric-adjacent data
  Used Software
  Attributes
    Description
      - Contains health information and derived data from voice (audio waveforms excluded in v1.0)

Acquisition Methods

- Name
    Data acquisition
  Used Software
  Attributes
    Description
      - Directly observed audio tasks (e.g., sustained phonation); clinical and questionnaire data collected via custom tablet application
    Was Directly Observed
      True
    Was Reported By Subjects
      True
    Was Inferred Derived
      True
    Was Validated Verified
      Standardized protocol; derived features computed from standardized audio; IRB approval

Collection Mechanisms

- Name
    Collection mechanisms
  Used Software
  Attributes
    Description
      - Custom tablet-based application; headset microphone when possible; standardized multi-site protocol

Data Collectors

- Name
    Data collection teams
  Used Software
  Attributes
    Description
      - Project investigators at specialty clinics across five North American sites

Collection Timeframes

- Name
    Session structure
  Used Software
  Attributes
    Description
      - Most participants completed data collection in a single session; a subset required multiple sessions

Ethical Reviews

- Name
    Ethics approvals
  Used Software
  Attributes
    Description
      - Data collection and sharing approved by the University of South Florida IRB; submitted to the University of Toronto Research Ethics Board

Data Protection Impacts
Preprocessing Strategies

- Name
    Audio standardization and feature derivation
  Used Software

    ID | Name | URL | Version
    --- | --- | --- | ---
    openSMILE | openSMILE | https://audeering.github.io/opensmile/ |
    Parselmouth | Parselmouth | https://github.com/YannickJadoul/Parselmouth |
    Praat | Praat | http://www.praat.org/ |
    Whisper-Large | OpenAI Whisper Large | https://github.com/openai/whisper |
    torchaudio | TorchAudio | https://pytorch.org/audio | 2.1
    librosa | librosa | https://librosa.org |
    b2aiprep | b2aiprep | https://github.com/sensein/b2aiprep |

  Attributes
    Description
      - Monaural conversion; resampling 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
      - Transcriptions via OpenAI Whisper Large

Cleaning Strategies
Labeling Strategies

- Name
    Transcription
  Used Software
    - ID
        Whisper-Large
      Name
        OpenAI Whisper Large
      URL
        https://github.com/openai/whisper
  Attributes
    Description
      - Automatic transcription for certain tasks; free-speech transcripts removed for de-identification

Raw Sources

- Name
    Raw audio availability
  Used Software
  Attributes
    Description
      - Original audio waveforms are not included in v1.0; planned for future releases with additional safeguards

Third Party Sharing

Name
  Third-party distribution
Description
  Yes. Distributed to credentialed users outside the hosting entity under registered access controls and a DUA.

Ip Restrictions
Regulatory Restrictions
Maintainers

- Name
    Hosting and support
  Used Software
  Attributes
    Description
      - Health Data Nexus
      - Temerty Centre for AI Research and Education in Medicine (Temerty Foundation-supported)

Errata
Retention Limit
Extension Mechanism
Is Tabular
Partially (tabular TSV/JSON metadata and features; spectrograms stored in Parquet)
Subsets

Description | ID | Media Type | Name | Path | Title
--- | --- | --- | --- | --- | ---
Parquet dataset with spectrograms (513×N) and identifiers (participant_id, session_id, task_name). | spectrograms.parquet | application/x-parquet | spectrograms.parquet | spectrograms.parquet | Derived spectrograms
Tab-delimited table of demographics, acoustic confounders, and validated questionnaire responses (on... | phenotype.tsv | text/tab-separated-values | phenotype.tsv | phenotype.tsv | Participant-level phenotype data
JSON data dictionary describing columns in phenotype.tsv. | phenotype.json | application/json | phenotype.json | phenotype.json | Phenotype data dictionary
Tab-delimited table of features derived from raw audio (one row per recording). | static_features.tsv | text/tab-separated-values | static_features.tsv | static_features.tsv | Recording-level static features
JSON data dictionary describing columns in static_features.tsv. | static_features.json | application/json | static_features.json | static_features.json | Static features data dictionary

🚀

## Uses

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

Tasks

- Name
    Intended tasks
  Used Software
  Attributes
    Response
      Voice-based biomarker discovery; disease state classification and screening; analysis of acoustic, phonetic, and prosodic features; model development and validation using derived speech representations.

Existing Uses

- Name
    First release status
  Used Software
  Attributes
    Description
      - v1.0 is the first public release; prior external uses not listed

Use Repository
Other Tasks

- Name
    Potential downstream tasks
  Used Software
  Attributes
    Description
      - Condition screening and monitoring using voice-derived features
      - Multimodal fusion with demographics/clinical variables
      - Robustness, fairness, and domain generalization studies for voice biomarkers

Future Use Impacts

- Name
    Use considerations
  Used Software
  Attributes
    Description
      - Cohort-based sampling may influence generalizability; users should account for cohort composition and site effects

License And Use Terms

Name
  Access and use terms
Used Software
Attributes
  Description
    - Access Policy
        only credentialed users who sign the DUA can access the files
    - License (files)
        Bridge2AI Voice Registered Access License
    - 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
License
Bridge2AI Voice Registered Access License
Version Access

Name
  Version access
Used Software
Attributes
  Description
    - Versioned records maintained via DOIs; latest-version DOI available for discovery

🔄

## Maintenance

How will the dataset be maintained?

Version
1.0
Updates

Name
  Update plan
Used Software
Attributes
  Description
    - Future releases aim to include voice waveforms with additional security safeguards
    - Versioned Dois Provided (latest Version DOI
        https://doi.org/10.57764/3sg0-7440)

Generated on 2025-11-09 10:17:35 using Bridge2AI Data Sheets Schema