# healthnexus tab references 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 clinical 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, bioacoustic database to understand disease like never before. | 3OT2OD032720-01S1

📊

## Composition

What do the instances represent?

Instances

1. Name
     Instance description
   Representation
     Voice recordings with derived spectrograms/features and participant-level phenotype/clinical data.
   Instance Type
     participants, sessions, and recordings (participant_id, session_id, task_name).
   Data Type
     Derived spectrogram arrays; acoustic, phonetic, and prosodic features; limited transcriptions; tabular phenotype and feature files.
   Counts
     12,523
   Label
     Cohort/disease group membership and clinical/phenotype variables; no raw audio included in v1.0.
   Sampling Strategies
     1. Name
          Targeted clinical cohort sampling
        Is Sample
          - sample from patients presenting at specialty clinics at five North American sites
        Is Random
          - False
        Source Data
          - Adults with conditions affecting voice (voice, neurological/neurodegenerative, mood/psychiatric, respiratory disorders)
        Is Representative
          - not stated
        Why Not Representative
          - Targeted sampling of specific disorders; pediatric cohort not included in v1.0
        Strategies
          - targeted clinical cohort sampling at participating sites

Subpopulations

- Name
    Cohort categories
  Identification
    - Disease Cohorts Identified At Enrollment
        Voice disorders; Neurological and Neurodegenerative; Mood and Psychiatric; Respiratory; Pediatric (planned but not included in v1.0).
  Distribution
    - Adult cohort only in v1.0; 306 participants across five sites in North America.

Distribution Formats

- Name
    Distribution formats
  Description
    - Parquet (spectrograms.parquet)
    - TSV (phenotype.tsv, static_features.tsv)
    - JSON (phenotype.json, static_features.json)

Distribution Dates

- Name
    Initial release
  Description
    - 2024-11-27 (v1.0)

🔍

## Collection Process

How was the data acquired?

ID *
doi:10.57764/qb6h-em84
Name
Bridge2AI-Voice v1.0
Title
Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information
Description
The Bridge2AI-Voice project presents a comprehensive, ethically sourced dataset enabling research on voice as a biomarker of health. Bridge2AI-Voice v1.0 provides 12,523 recordings for 306 adult participants collected across five sites in North America, with corresponding demographic, clinical, and validated questionnaire information. The initial release is considered low risk and includes derived data (e.g., spectrograms, acoustic/phonetic/prosodic features) and data dictionaries; original voice audio waveforms are not included. Participants were enrolled in predetermined groups reflecting conditions that manifest in voice (voice disorders, neurological and neurodegenerative disorders, mood and psychiatric disorders, respiratory disorders), with pediatric cohorts planned but not included in v1.0. Data were collected via a standardized protocol and subsequently de-identified using HIPAA Safe Harbor principles.
Language
en
Issued
2024-11-27
Page
https://doi.org/10.57764/qb6h-em84
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

Keywords

- voice
- bridge2ai
- audio
- biomarker
- spectrograms
- clinical
- health

Addressing Gaps

- Name
    AddressingGap
  Response
    Address the lack of large, high-quality, multi-institutional, demographically diverse voice datasets linked to health and clinical data.

Sensitive Elements

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

Is Deidentified

Name
  De-identification status
Description
  - HIPAA Safe Harbor identifiers removed (e.g., names, contact details, finer-than-year dates, identifiers).
  - State and province removed; country of data collection retained.
  - Transcripts of free speech audio removed.
  - Original audio waveforms omitted in v1.0; only derived spectrograms and features released.

Acquisition Methods

1. Name
     Data acquisition
   Description
     - Standardized protocol at specialty clinics; demographic, clinical, and validated questionnaires; voice tasks (e.g., sustained vowel).
     - Custom tablet application used; headset microphone when possible.
     - Some participants completed multiple sessions.
   Was Directly Observed
     yes (voice recordings)
   Was Reported By Subjects
     yes (validated questionnaires)
   Was Inferred Derived
     yes (spectrograms, acoustic/phonetic/prosodic features, transcriptions)
   Was Validated Verified
     Standardized data collection protocol; IRB/REB oversight.

Collection Mechanisms

- Name
    Collection mechanisms
  Description
    - Custom tablet application for standardized data capture; headset microphone when feasible.
    - Export and conversion from REDCap using an open-source b2aiprep library.
  Used Software

    Name | URL | Version
    --- | --- | ---
    REDCap |  | 3.20.0
    b2aiprep | https://github.com/sensein/b2aiprep |

Data Collectors

- Name
    Data collection team
  Description
    - Project investigators at five North American clinical sites.

Ethical Reviews

- Name
    Ethics and 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
    - Raw audio converted to mono and resampled to 16 kHz with a Butterworth anti-aliasing filter.
    - Spectrograms computed via STFT with 25 ms window, 10 ms hop, 512-point FFT.
    - Acoustic features via OpenSMILE; phonetic/prosodic features via Parselmouth and Praat.
    - Transcriptions generated with OpenAI's Whisper Large model (free-speech transcripts later removed from release).
  Used Software

    Name | Version
    --- | ---
    OpenSMILE |
    Parselmouth |
    Praat |
    Torchaudio | 2.1
    OpenAI Whisper Large |

Cleaning Strategies

- Name
    De-identification and release filtering
  Description
    - HIPAA Safe Harbor removal; state/province removed; country retained.
    - Free-speech transcripts removed; only derived data released (no raw audio).

Labeling Strategies

- Name
    Transcription
  Description
    - Automatic transcriptions generated using OpenAI's Whisper Large model; free-speech transcripts removed prior to release.
  Used Software
    - Name
        OpenAI Whisper Large

Raw Sources

- Name
    Raw audio availability
  Description
    - Raw audio waveforms are not included in v1.0; only spectrograms and derived features are provided. Future releases aim to include voice waveforms with additional security precautions.

External Resources

1. Name
     External resources
   External Resources
     - Documentation Website
         https://docs.b2ai-voice.org
     - Zenodo Record (bridge2ai Voice Redcap V3.20.0)
         https://doi.org/10.5281/zenodo.14148755
     - B2aiprep Preprocessing Library
         https://github.com/sensein/b2aiprep
   Archival
     - Version-specific and latest DOIs provided.
   Restrictions
     - Registered, credentialed access; signed DUA and training required.

Retention Limit

Name
  Retention limits
Description
  - Not specified in source.

Is Tabular
mixed (tabular TSV/JSON dictionaries and array-based Parquet spectrograms)
Subsets

Description | ID | Media Type | Name | Path | Title
--- | --- | --- | --- | --- | ---
Parquet dataset containing 513xN spectrograms per recording with participant_id, session_id, and tas... | spectrograms.parquet | application/x-parquet | spectrograms.parquet | spectrograms.parquet | Spectrograms derived from voice waveforms
Tab-delimited participant-level demographics, acoustic confounders, and validated questionnaire resp... | 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 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

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## Uses

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

Tasks

- Name
    Task
  Response
    AI/ML research on voice-based biomarkers for disease screening, monitoring, and prognosis.

Other Tasks

- Name
    Potential uses
  Description
    - Disease screening and therapeutic monitoring for respiratory, voice, neurological, and mood/psychiatric disorders.
    - Development and evaluation of AI methods for voice analysis.

Future Use Impacts

- Name
    Considerations for future use
  Description
    - v1.0 includes only derived features and spectrograms (no raw audio), which may limit tasks requiring waveforms.
    - Free-speech transcripts removed.
    - Adult-only dataset in v1.0; pediatric cohort not yet included.

License And Use Terms

- Name
    Access and licensing
  Description
    - License
        Bridge2AI Voice Registered Access License.
    - Access Policy
        Only credentialed users who sign the 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
  Versioning and access to older versions
Description
  - Versioned DOI (v1.0)
      https://doi.org/10.57764/qb6h-em84
  - Latest Version DOI
      https://doi.org/10.57764/3sg0-7440

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## Maintenance

How will the dataset be maintained?

Version
1.0
Last Updated On
2024-11-27
Updates

Name
  Update plan
Description
  - Future releases aim to include original voice audio waveforms with additional security measures; see latest DOI for updates.

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