# physionet b2ai-voice 1.1 d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

- ID
    purpose-1
  Name
    Purpose
  Response
    Create an ethically sourced, diverse voice dataset linked to health information to enable AI research on voice as a biomarker and support clinical insights across multiple disease areas.

Funders

Grantor | Grant Name | Grant Number
--- | --- | ---
National Institutes of Health (NIH) | Bridge2AI: Voice as a Biomarker of Health | 3OT2OD032720-01S1

📊

## Composition

What do the instances represent?

Instances

Counts | Data Type | ID | Instance Type | Missing Information | Name | Representation | Sampling Strategies
--- | --- | --- | --- | --- | --- | --- | ---
12523 | Derived features only: spectrograms (513×N), MFCCs (60×N), static acoustic features (one row per rec... | inst-recordings | Recordings (per session and task) | {'id': 'miss-1', 'name': 'Missing Info', 'missing': ['Original audio waveforms', 'Free speech transcripts'], 'why_missing': ['Privacy protection and de-identification; reduce re-identification risk']} | Recording-derived instances | Derived data from voice recordings (e.g., spectrograms, MFCCs, static features) | {'id': 'samp-1', 'name': 'Sampling Strategy', 'is_sample': ['yes'], 'is_random': ['no'], 'source_data': ['Patients at specialty clinics across five North American sites'], 'is_representative': ['unknown'], 'representative_verification': ['not specified'], 'why_not_representative': ['Participants selected based on membership in predefined disease cohorts rather than population sampling.\n'], 'strategies': ['Deterministic clinical cohort enrollment per standardized protocol']}
306 | Demographics, clinical variables, validated questionnaires (phenotype.tsv/json) | inst-participants | Participants |  | Participant instances | Participants with linked phenotype and questionnaire data |

Subpopulations

Distribution | ID | Identification | Name
--- | --- | --- | ---
Not specified | subpop-1 | Adult participants in specialty clinics | Adult cohort
Not specified | subpop-2 | Voice disorders, Neurological and neurodegenerative disorders, ... (+3 more) | Disease cohorts

Distribution Formats

- ID
    distfmt-1
  Name
    Distribution Formats
  Description
    - Parquet (.parquet)
        spectrograms.parquet, mfcc.parquet
    - Tsv (.tsv)
        phenotype.tsv, static_features.tsv
    - Json (.json)
        phenotype.json, static_features.json

Distribution Dates

- ID
    distdate-1
  Name
    Distribution Date
  Description
    - 2025-01-17

🔍

## Collection Process

How was the data acquired?

ID *
bridge2ai-voice-v1.1
Name
Bridge2AI-Voice v1.1
Title
Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information
Description
Bridge2AI-Voice is a comprehensive, ethically sourced dataset derived from voice recordings linked to clinical information to enable research on voice as a biomarker of health. Version 1.1 provides derived data (e.g., spectrograms, MFCCs, static acoustic features) and rich phenotype information for a cohort initially comprising adults. The initial release (v1.0) included 12,523 recordings from 306 participants collected across five sites in North America, selected from five disease cohort categories (voice disorders, neurological/neurodegenerative disorders, mood/psychiatric disorders, respiratory disorders, and pediatric; v1.1 contains adult cohort data). To reduce re-identification risk, only derived data are shared in this version; raw audio waveforms are excluded. Data collection followed a standardized, multi-site protocol, with de-identification aligned to HIPAA Safe Harbor.
Page
https://doi.org/10.13026/249v-w155
Issued
2025-01-17
Keywords

- voice
- Bridge2AI
- spectrograms
- MFCC
- bioacoustics
- clinical data
- derived features
- registered access
- HIPAA Safe Harbor
- Parquet
- phenotype

Created By

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

Addressing Gaps

- ID
    gap-1
  Name
    Addressing Gap
  Response
    Addresses the lack of large, high-quality, ethically sourced, multi-institutional, and demographically diverse voice datasets linked to clinical and questionnaire data for reproducible AI research.

Sampling Strategies

1. ID
     samp-2
   Name
     Sampling Strategy (dataset level)
   Is Sample
     - yes
   Is Random
     - no
   Source Data
     - Specialty clinics across five North American sites
   Is Representative
     - unknown
   Representative Verification
     - not specified
   Strategies
     - Clinical cohort-based enrollment according to inclusion/exclusion criteria

Anomalies
External Resources

1. ID
     ext-1
   Name
     External Resources
   External Resources
     - Project Website And Documentation
         https://docs.b2ai-voice.org
     - Raw Audio Access Requests
         DACO@b2ai-voice.org (controlled access)
   Future Guarantees
     - Raw audio via controlled access to protect participant privacy
   Archival
     - DOI-resolved project page on PhysioNet
   Restrictions
     - Registered access license and data use agreement required

Confidential Elements

- ID
    conf-1
  Name
    Confidentiality
  Description
    - Contains clinical and demographic data; raw audio excluded to reduce risk; access controlled via registered access and DUA

Content Warnings
Sensitive Elements

- ID
    sens-1
  Name
    Sensitive Elements
  Description
    - Health-related clinical data and demographics may be considered sensitive

Is Deidentified

ID
  deid-1
Name
  Deidentification
Description
  - HIPAA Safe Harbor identifiers removed (e.g., names, fine-grained dates, contact numbers, biometric identifiers, etc.)
  - State and province removed; country of data collection retained
  - Free speech transcripts removed
  - Audio waveforms omitted; only derived features are shared in this version

Acquisition Methods

1. ID
     acq-1
   Name
     Instance Acquisition
   Description
     - Voice recordings collected during clinic visits; phenotype gathered via standardized questionnaires
   Was Directly Observed
     yes
   Was Reported By Subjects
     yes
   Was Inferred Derived
     yes
   Was Validated Verified
     yes

Collection Mechanisms

- ID
    coll-1
  Name
    Collection Mechanisms
  Description
    - Standardized multi-site protocol; custom tablet application for data capture; headset used when possible; data managed via REDCap and exported with open-source tooling

Data Collectors

- ID
    dc-1
  Name
    Data Collectors
  Description
    - Project investigators at specialty clinics across five North American sites

Ethical Reviews

- ID
    irb-1
  Name
    Ethical Review
  Description
    - Data collection and sharing approved by the University of South Florida Institutional Review Board

Data Protection Impacts

- ID
    dpia-1
  Name
    Data Protection
  Description
    - Privacy protections include HIPAA Safe Harbor de-identification, omission of raw audio and free speech transcripts, and registered/controlled access to sensitive materials

Preprocessing Strategies

1. ID
     prep-1
   Name
     Audio preprocessing and feature extraction
   Description
     - Raw audio converted to mono and resampled to 16 kHz with a Butterworth anti-aliasing filter; derived spectrograms computed (25 ms window, 10 ms hop, 512-point FFT); 60 MFCCs extracted from spectrograms; static acoustic and prosodic/phonetic features computed with open-source tools; transcriptions generated using Whisper Large
   Used Software

     ID | Name
     --- | ---
     sw-opensmile | openSMILE
     sw-praat | Praat
     sw-parselmouth | Parselmouth (Python interface to Praat)
     sw-torchaudio | torchaudio
     sw-whisper | OpenAI Whisper Large
     sw-b2aiprep | b2aiprep (processing library)

Cleaning Strategies

- ID
    clean-1
  Name
    De-identification and redaction
  Description
    - Removal of HIPAA Safe Harbor identifiers; removal of state/province; removal of free speech transcripts; exclusion of raw audio from shared dataset

Labeling Strategies

- ID
    lab-1
  Name
    Transcription and annotations
  Description
    - Transcriptions generated using OpenAI Whisper Large; free speech transcripts were not shared in this release to protect privacy

Raw Sources

- ID
    raw-1
  Name
    Raw Data Availability
  Description
    - Original raw audio data available via controlled access upon request to DACO@b2ai-voice.org; shared dataset contains derived features only

Ip Restrictions
Regulatory Restrictions
Maintainers

- ID
    maint-1
  Name
    Maintainer
  Description
    - Hosted on PhysioNet by the MIT Laboratory for Computational Physiology

Errata
Retention Limit
Extension Mechanism
Is Tabular
Partially (TSV and JSON metadata; Parquet arrays for derived features)
🚀

## Uses

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

Tasks

- ID
    task-1
  Name
    Intended Task
  Response
    Develop and evaluate AI methods for health-related inference from voice, including detection and characterization of conditions associated with acoustic changes (e.g., voice, neurological, mood, and respiratory disorders) using derived features (spectrograms, MFCCs) and phenotype data.

Existing Uses
Use Repository

- ID
    repo-1
  Name
    Project Website
  Description
    - https://docs.b2ai-voice.org

Other Tasks

- ID
    other-1
  Name
    Potential Uses
  Description
    - Benchmarking AI models for acoustic biomarker discovery, condition screening, and monitoring using derived voice features linked with phenotype data

Future Use Impacts

- ID
    fut-1
  Name
    Future Use Considerations
  Description
    - Use may be limited for tasks requiring raw waveforms or free speech transcripts due to privacy protections; v1.1 includes adults only which may affect generalizability to pediatric populations

Discouraged Uses
License And Use Terms

ID
  lic-terms-1
Name
  License and Terms of Use
Description
  - Access Policy
      Only registered users who sign the specified data use agreement can access the files
  - License
      Bridge2AI Voice Registered Access License
  - Data Use Agreement
      Bridge2AI Voice Registered Access Agreement
  - Raw audio disseminated via controlled access to protect participant privacy

📤

## Distribution

How will the dataset be distributed?

DOI
doi:10.13026/249v-w155
License
Bridge2AI Voice Registered Access License
Version Access

ID
  veracc-1
Name
  Version Access
Description
  - Older versions listed on PhysioNet; files for version 1.1 are no longer available; latest version as of the page is 2.0.1

🔄

## Maintenance

How will the dataset be maintained?

Version
1.1
Updates

ID
  update-1
Name
  Update Plan
Description
  - Version History
      v1.0 (initial release), v1.1 (added MFCCs)
  - Future Plan
      aim to include voice data in future releases with additional security precautions

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