# healthnexus tab conflicts-of-interest d4d

Datasheet for Dataset - Human Readable Format

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## Motivation

Why was the dataset created?

Purposes

- Name
    Purpose
  Response
    Create an ethically sourced flagship dataset to enable AI research on the use of voice as a biomarker of health by linking diverse voice recordings with clinical and demographic information.

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 | 3OT2OD032720-01S1

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## Composition

What do the instances represent?

Instances

1. Name
     Instance class
   Representation
     Voice recordings linked to participant-level clinical, demographic, and questionnaire data; derived spectrogram matrices and acoustic/phonetic/prosodic features per recording.
   Instance Type
     Participants, recording sessions, and recordings (per task); derived data instances per recording.
   Data Type
     Derived features (e.g., spectrograms, acoustic, phonetic, prosodic) from standardized audio; raw audio waveforms are withheld in v1.0.
   Counts
     12,523

Subpopulations

- Name
    Adult cohort
  Identification
    - Adult participants meeting inclusion criteria within predefined disease cohorts
  Distribution
    - 306 participants; 12,523 recordings across multiple recording tasks

Distribution Formats

- Description
    - Parquet (.parquet) for spectrograms
    - Tab-delimited text (.tsv) for phenotype and static features
    - JSON (.json) data dictionaries

Distribution Dates

- Description
    - 2024-11-27 (initial public release v1.0)

Distribution
🔍

## 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 v1.0 is an ethically sourced, multi-institutional voice dataset focused on the use of voice as a biomarker of health. The initial release provides 12,523 recordings for 306 adult participants collected across five sites in North America. Participants were selected from five predefined cohorts where voice/speech changes are associated with disease: voice disorders, neurological/neurodegenerative disorders, mood/psychiatric disorders, respiratory disorders, and pediatric voice/speech disorders (note: v1.0 includes adults only). This release contains low-risk derived data (e.g., spectrograms and acoustic/phonetic/prosodic features) and corresponding demographic, clinical, and validated questionnaire data; raw audio waveforms are not included in v1.0. Documentation: "https://docs.b2ai-voice.org"
Page
https://doi.org/10.57764/qb6h-em84
Issued
2024-11-27
Keywords

- voice
- bridge2ai
- audio
- health
- biomarker

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
    Address the lack of large, high-quality, multi-institutional, diverse voice datasets linked to other health biomarkers and collected under standardized, ethically governed protocols.

Sampling Strategies

1. Name
     Cohort sampling strategy
   Is Sample
     - True
   Is Random
     - False
   Source Data
     - Patients at specialty clinics across five sites in North America
   Is Representative
     - False
   Why Not Representative
     - Participants were recruited based on membership in predefined disease cohorts (voice, neurological, mood/psychiatric, respiratory, pediatric), and v1.0 includes adult cohort only.
   Strategies
     - Purposive cohort-based sampling within specialty clinics

Sensitive Elements

- Description
    - Health-related clinical information and demographics are included; identifiers removed per HIPAA Safe Harbor.

Acquisition Methods

1. Description
     - Data were collected at specialty clinics using a standardized protocol capturing demographics, health questionnaires (including validated instruments), targeted confounder questions, disease-specific information, and voice tasks (e.g., sustained vowel).
     - Data reported by subjects (questionnaires) and directly observed (voice recordings); some data are indirectly derived (features, transcriptions).
   Was Directly Observed
     yes (voice recordings)
   Was Reported By Subjects
     yes (questionnaires)
   Was Inferred Derived
     yes (features, transcriptions)

Collection Mechanisms

- Description
    - Custom tablet-based data collection application; headset used for recording when possible; data exported from REDCap using an open-source library developed by the team.
  Used Software

    Name
    Bridge2AI-Voice tablet data collection app
    REDCap
    b2aiprep

Data Collectors

- Description
    - Project investigators and clinical teams at five North American sites

Ethical Reviews

- Description
    - Data collection and sharing approved by the University of South Florida Institutional Review Board; submission to the University of Toronto Research Ethics Board noted.

Preprocessing Strategies

- Description
    - Raw audio converted to monaural, resampled to 16 kHz with a Butterworth anti-aliasing filter; spectrograms computed via STFT (25 ms window, 10 ms hop, 512-point FFT).
    - Acoustic features extracted with OpenSMILE; phonetic/prosodic features computed with Parselmouth and Praat; transcriptions generated using OpenAI Whisper Large.
    - Code to preprocess and merge source data provided via the b2aiprep library.
  Used Software

    Name
    openSMILE
    Parselmouth
    Praat
    torchaudio
    OpenAI Whisper Large
    b2aiprep

Cleaning Strategies

- Description
    - HIPAA Safe Harbor identifiers removed; state/province removed; country retained.
    - Transcripts of free speech audio removed from the release.
    - Only derived data (e.g., spectrograms, features) included in v1.0; audio waveforms omitted.

Labeling Strategies

- Description
    - Automated transcriptions generated using OpenAI Whisper Large; transcripts of free speech audio not released in v1.0.
  Used Software
    - Name
        OpenAI Whisper Large

Raw Sources

- Description
    - Raw voice audio collected but withheld from v1.0 distribution; planned for future releases with additional safeguards.

Maintainers

- Description
    - Health Data Nexus (Temerty Centre for AI Research and Education in Medicine)

Is Deidentified

Description
  - HIPAA Safe Harbor de-identification applied; removal of direct identifiers and fine-grained dates; state/province removed; country retained; free-speech transcripts removed; no raw audio in v1.0.

Is Tabular
partial (tabular phenotype/features; array-based spectrograms)
External Resources

- External Resources
    - Project Documentation Website
        https://docs.b2ai-voice.org
    - Publication/record landing via DOI
- Archival
    - Versioned DOIs indicate archival/versioning support via persistent identifiers
- Restrictions
    - Registered access with DUA and required training

Subsets

Description | ID | Media Type | Name | Path | Title
--- | --- | --- | --- | --- | ---
Parquet dataset containing 513 x N spectrogram matrices per recording, with participant_id, session_... | bridge2ai-voice-v1.0-spectrograms | application/x-parquet | spectrograms.parquet | spectrograms.parquet | Derived spectrograms
Tab-delimited file with one row per participant including demographics, acoustic confounders, and re... | bridge2ai-voice-v1.0-phenotype | text/tab-separated-values | phenotype.tsv | phenotype.tsv | Participant phenotype and questionnaires
JSON data dictionary mapping column names to descriptions for phenotype.tsv. | bridge2ai-voice-v1.0-phenotype-dict | application/json | phenotype.json | phenotype.json | Phenotype data dictionary
Tab-delimited file with one row per unique recording; includes features derived using openSMILE, Pra... | bridge2ai-voice-v1.0-static-features | text/tab-separated-values | static_features.tsv | static_features.tsv | Recording-level static features
JSON data dictionary mapping feature column names to descriptions for static_features.tsv. | bridge2ai-voice-v1.0-static-features-dict | 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
    Support AI-driven analysis of voice (e.g., feature extraction, modeling, and evaluation) for health-related research across disease cohorts where voice/speech changes are clinically relevant.

Future Use Impacts

- Description
    - Restricting v1.0 to low-risk derived data (no raw audio) mitigates privacy risks but may limit certain modeling tasks requiring waveforms; future releases aim to include audio with additional safeguards.

License And Use Terms

Name
  Bridge2AI Voice Registered Access
Description
  - Access restricted to credentialed users who sign the Bridge2AI Voice Registered Access Agreement (DUA) under the Bridge2AI Voice Registered Access License.
  - Required Training
      TCPS 2: CORE 2022.
  - Access Platform
      Health Data Nexus (credentialed access).

📤

## Distribution

How will the dataset be distributed?

DOI
doi:10.57764/qb6h-em84
License
Bridge2AI Voice Registered Access License
Version Access

Description
  - Version Specific DOI
      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
Updates

Description
  - Future releases planned to include raw voice data with additional security and privacy precautions; ongoing additions and corrections anticipated.

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