# healthnexus tab versions 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 AI research on voice as a biomarker of health.

Funders

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

📊

## Composition

What do the instances represent?

Instances

1. Name
     Instance description
   Representation
     Voice-derived data linked to demographic, clinical, and validated questionnaire information.
   Instance Type
     Participants with one or more recording sessions; one row per recording in features; one row per participant in phenotype.
   Data Type
     Derived data including: - Spectrograms (513 x N time-frequency representations from 16 kHz monaural audio) - Acoustic features (e.g., openSMILE) - Phonetic/prosodic features (e.g., Praat/Parselmouth) - Phenotype/demographics/clinical/questionnaire responses Note: Raw audio waveforms are not included in v1.0.
   Counts
     12,523
   Label
     Task identifiers (task_name) per recording; no explicit diagnostic labels distributed in v1.0.
   Sampling Strategies
     1. Name
          Sampling
        Is Sample
          - Yes; participants selected from specialty clinics.
        Is Random
          - No; condition-based targeted enrollment.
        Source Data
          - Patients presenting at participating specialty clinics across five North American sites.
        Is Representative
          - Not intended to be representative of the general population; targeted by condition cohorts.
        Why Not Representative
          - Cohort design targets specific diseases and clinical populations.
        Strategies
          - Targeted clinical cohort recruitment based on predefined disease categories (voice, neurological/neurodegenerative, mood/psychiatric, respiratory; pediatric planned but not included in v1.0).

Subpopulations

Distribution | Identification | Name
--- | --- | ---
Distribution by cohort not provided in the release page. | Participants selected into disease cohort categories (voice disorders, neurological/neurodegenerative disorders, mood/psychiatric disorders, respiratory disorders). | Disease cohorts
Pediatric cohort planned for future releases; not present in v1.0. | As of v1.0, only adult participants are included. | Adult cohort v1.0

Distribution Formats

- Name
    Formats
  Description
    - Parquet (.parquet) for spectrograms
    - TSV (.tsv) for phenotype and static features
    - JSON (.json) data dictionaries for phenotype and features

Distribution Dates

- Name
    DistributionDate
  Description
    - 2024-11-27

🔍

## Collection Process

How was the data acquired?

ID *
bridge2ai-voice-1.0
Name
Bridge2AI-Voice
Title
Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information
Description
Bridge2AI-Voice v1.0 is a comprehensive collection of data derived from voice recordings with corresponding clinical information to enable research on voice as a biomarker of health. 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. As of v1.0, only data from the adult cohort is available. This initial release contains data considered low risk, including derivations such as spectrograms and engineered features, but not the original voice recordings. Detailed demographic, clinical, and validated questionnaire data are also made available. Data collection used a standardized protocol with a custom tablet application, headset recording when possible, and REDCap; preprocessing included resampling to 16 kHz with a Butterworth anti-aliasing filter and derivation of spectrograms and acoustic/phonetic/prosodic features.
Language
English
Issued
2024-11-27
Page
https://doi.org/10.57764/qb6h-em84
Keywords

- voice
- bridge2ai
- audio
- biomarker
- spectrogram
- clinical

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
    AddressingGap
  Response
    Addresses the need for a large, high-quality, diverse, multi-institutional voice dataset linked to other health biomarkers with standardized data collection, ethical sourcing, and detailed clinical/phenotypic context.

Creators
Sampling Strategies

1. Name
     Cohort sampling
   Is Sample
     - Yes; clinical cohort-based sample.
   Is Random
     - No.
   Source Data
     - Specialty clinic patients screened against inclusion/exclusion criteria and consented.
   Is Representative
     - Not of the general population; designed for disease-relevant cohorts.
   Representative Verification
     - Standardized protocol across sites; not intended as population-representative sampling.
   Strategies
     - Deterministic cohort selection based on predefined conditions.

Anomalies

- Name
    DataAnomaly
  Description
    - None reported in the release notes.

External Resources

1. Name
     Documentation and tooling
   External Resources
     - https://docs.b2ai-voice.org
     - https://github.com/sensein/b2aiprep
   Future Guarantees
     - Not specified.
   Archival
     - Not specified.
   Restrictions
     - None beyond dataset access controls for data files.

Confidential Elements

- Name
    Confidentiality
  Description
    - Dataset is released in de-identified, low-risk form; original voice recordings and free-speech transcripts are not included in v1.0.

Content Warnings

- Name
    ContentWarning
  Warnings
    - None noted.

Sensitive Elements

- Name
    Sensitive elements
  Description
    - Clinical and health-related questionnaire responses.
    - Voice-related features may be considered biometric information.

Is Deidentified

Name
  Deidentification
Description
  - HIPAA Safe Harbor identifiers removed.
  - State and province removed; country of data collection retained.
  - Free speech transcripts removed.
  - Raw audio waveforms omitted; only derived spectrograms and features included in v1.0.
  - Dataset characterized as low risk for this initial release.

Acquisition Methods

1. Name
     Acquisition
   Description
     - Directly observed voice recordings; subject-reported validated questionnaires; derived features from raw audio.
   Was Directly Observed
     True
   Was Reported By Subjects
     True
   Was Inferred Derived
     True
   Was Validated Verified
     True

Collection Mechanisms

- Name
    CollectionMechanism
  Description
    - Standardized multi-site protocol; custom tablet application; headset used when possible; data captured into REDCap and exported; preprocessing and merges performed with the open-source b2aiprep library.
  Used Software

    Name | URL | Version
    --- | --- | ---
    Bridge2AI Voice REDCap | https://doi.org/10.5281/zenodo.14148755 | v3.20.0
    b2aiprep | https://github.com/sensein/b2aiprep |

Data Collectors

- Name
    DataCollector
  Description
    - Project investigators at participating specialty clinics; screening against inclusion/exclusion criteria; patient consent obtained prior to data collection.

Collection Timeframes
Ethical Reviews

- Name
    EthicalReview
  Description
    - Data collection and sharing approved by the University of South Florida Institutional Review Board (IRB).
    - Submitted for review to the University of Toronto Research Ethics Board (REB).

Data Protection Impacts
Preprocessing Strategies

- Name
    Preprocessing
  Description
    - Raw audio converted to monaural, resampled to 16 kHz with a Butterworth anti-aliasing filter.
    - Spectrograms computed with STFT (25 ms window, 10 ms hop, 512-point FFT).
    - Acoustic features extracted (e.g., openSMILE); phonetic/prosodic features computed (Praat/Parselmouth); additional features via torchaudio.
  Used Software

    Name
    openSMILE
    Praat
    Parselmouth
    torchaudio
    b2aiprep

Cleaning Strategies

- Name
    Cleaning
  Description
    - De-identification per HIPAA Safe Harbor; removal of state/province; removal of free speech transcripts; omission of original audio waveforms for v1.0.

Labeling Strategies

- Name
    Labeling
  Description
    - Automatic speech transcriptions generated using Whisper Large during processing; free speech transcripts were removed prior to release.
  Used Software
    - Name
        OpenAI Whisper Large

Raw Sources

- Name
    RawData
  Description
    - Raw audio waveforms were not released in v1.0; only derived representations (spectrograms and features) are distributed.

Ip Restrictions

Name
  IPRestrictions
Description
  - None stated beyond the registered access license and DUA requirements.

Regulatory Restrictions
Maintainers

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

Errata
Retention Limit
Extension Mechanism
Is Tabular
Mixed; spectrograms in Parquet, features and phenotype in TSV with JSON data dictionaries.
🚀

## Uses

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

Tasks

- Name
    Task
  Response
    AI method development and evaluation for detecting or characterizing health conditions from voice-derived representations (e.g., classification across disease cohorts).

Existing Uses
Use Repository
Other Tasks

- Name
    OtherTask
  Description
    - Benchmarking of voice-based health AI models; feature analysis and biomarker discovery; method development for fair, robust voice-based health inference.

Future Use Impacts

- Name
    FutureUseImpact
  Description
    - Initial release omits raw audio to reduce privacy risk; users should consider potential sensitivity of voice-derived biometric features and clinical phenotypes in downstream applications.

Discouraged Uses
License And Use Terms

Name
  LicenseAndUseTerms
Description
  - License
      Bridge2AI Voice Registered Access License.
  - Access requires signing the Bridge2AI Voice Registered Access Agreement (DUA).
  - Access Is Restricted To Credentialed Users Who Complete 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
🔄

## Maintenance

How will the dataset be maintained?

Version
1.0
Updates

Name
  UpdatePlan
Description
  - Future releases aim to include original voice recordings with additional precautions to ensure data security; pediatric cohort planned for future inclusion.

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