# healthnexus tab citationModal d4d

Datasheet for Dataset - Human Readable Format

🎯

## Motivation

Why was the dataset created?

Purposes

1. ID
     purpose-1
   Name
     Dataset purpose
   Description
     Enable AI research into voice as a biomarker of health across multiple clinical conditions using ethically sourced, diverse, multi-institutional data linked to health information.
   Response
     Create an ethically sourced, diverse voice dataset linked to clinical information to accelerate AI research on voice as a biomarker of health.

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 like never before | 3OT2OD032720-01S1

📊

## Composition

What do the instances represent?

Instances

Counts | Data Type | ID | Instance Type | Label | Missing Information | Name | Representation | Sampling Strategies
--- | --- | --- | --- | --- | --- | --- | --- | ---
12523 | Derived features from raw audio including spectrograms and acoustic/phonetic/prosodic features. | inst-recordings | Recordings (per session and task) | Task names per recording (e.g., sustained phonation vowel tasks); no raw audio included in v1.0. | {'id': 'miss-1', 'name': 'Removed elements', 'missing': ['Raw audio waveforms (omitted in v1.0)', 'Transcripts of free speech audio'], 'why_missing': ['Privacy and low-risk release; de-identification measures']} | Voice-derived recordings | Voice recordings-derived data (spectrograms and engineered features) aligned to session and task met... | {'id': 'samp-1', 'name': 'Cohort sampling', 'is_sample': [True], 'is_random': [False], 'source_data': ['Patients presenting at specialty clinics/institutions across five North American sites'], 'is_representative': ['not specified'], 'strategies': ['Targeted enrollment of five predetermined clinical groups (respiratory, voice, neurological, mood/psychiatric, pediatric)']}
306 | Demographics, acoustic confounders, validated questionnaires, disease-specific information collected... | inst-participants | Participants (adult cohort in v1.0) | Disease cohort categories and clinical attributes captured in phenotype file. |  | Participants | Individual participants with linked demographic, clinical, and questionnaire data. |

Subpopulations

Distribution | ID | Identification | Name
--- | --- | --- | ---
Not specified in this record | subpop-1 | v1.0 includes only adult participants | Adult cohort
Per-group counts not specified in this record | subpop-2 | Voice disorders, Neurological and neurodegenerative disorders, ... (+3 more) | Clinical condition groups

Distribution Formats

Description | ID | Name
--- | --- | ---
Credentialed access via Health Data Nexus portal; files available after DUA and required training completion | dist-portal | Distribution channel
Parquet (spectrograms), TSV (phenotype and static features), JSON (data dictionaries) | dist-formats | File formats

Distribution Dates

- ID
    distdate-1
  Name
    Initial public release
  Description
    - 2024-11-27 (v1.0)

🔍

## Collection Process

How was the data acquired?

ID *
b2ai-voice-v1.0
Name
Bridge2AI-Voice
Title
Bridge2AI-Voice: An ethically-sourced, diverse voice dataset linked to health information v1.0
Description
The Bridge2AI-Voice project seeks to create an ethically sourced flagship dataset to enable future research in artificial intelligence and support critical insights into the use of voice as a biomarker of health. Bridge2AI-Voice v1.0 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. The initial release contains data considered low risk, including derivations such as spectrograms (not the original voice recordings), as well as detailed demographic, clinical, and validated questionnaire data.
Page
https://doi.org/10.57764/qb6h-em84
Issued
2024-11-27
Created On
2024-11-27
Language
English
Keywords

- voice
- bridge2ai
- audio
- spectrograms
- phenotype
- parquet
- tsv
- health

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

Status
bibo:draft
Addressing Gaps

1. ID
     gap-1
   Name
     Gaps addressed
   Description
     Addresses limitations of prior work with small datasets, limited demographic diversity, and non-standardized protocols.
   Response
     Provides a large, multi-institutional, standardized, ethically sourced dataset with diverse demographics and linked clinical information.

Acquisition Methods

1. ID
     acq-1
   Name
     Data acquisition
   Description
     - Standardized protocol with demographic information, health questionnaires, targeted acoustic confounders, disease-specific information, and voice recording tasks (e.g., sustained vowel phonation)
     - Data exported from REDCap and converted using an open-source library developed by the team
   Was Directly Observed
     yes (voice tasks recorded via headset/tablet app)
   Was Reported By Subjects
     yes (validated questionnaires and self-reported items)
   Was Inferred Derived
     yes (acoustic/phonetic/prosodic features and spectrograms derived from raw audio; ASR transcriptions generated then removed for free speech)
   Was Validated Verified
     yes (standardized multi-site protocol and IRB/REB oversight)

Collection Mechanisms

- ID
    mech-1
  Name
    Collection mechanisms
  Description
    - Custom tablet application for data capture; headset used when possible
    - Data managed in REDCap; conversion and preprocessing via open-source b2aiprep library
    - Standardized tasks including sustained phonation

Data Collectors

- ID
    collectors-1
  Name
    Data collectors
  Description
    - Project investigators at specialty clinics and institutions; participants screened for inclusion/exclusion prior to visit; consent obtained

Collection Timeframes

- ID
    timeframe-1
  Name
    Collection timeframe
  Description
    - Data collected across five sites in North America; specific collection dates not provided in this record; first public release on 2024-11-27

Ethical Reviews

Description | ID | Name
--- | --- | ---
Data collection and sharing approved by the University of South Florida Institutional Review Board | ethics-usf | IRB approval (USF)
Submission to the University of Toronto Research Ethics Board for review | ethics-utoronto | REB submission (U of Toronto)

Preprocessing Strategies

1. ID
     prep-1
   Name
     Audio preprocessing and feature derivation
   Description
     - Raw audio converted to monaural and 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 and prosodic features computed using Parselmouth and Praat (e.g., F0, formants, voice quality)
     - Transcriptions generated with OpenAI Whisper Large (free speech transcripts later removed from release)
   Used Software

     ID | Name | URL | Version
     --- | --- | --- | ---
     sw-opensmile | openSMILE | https://www.audeering.com/research/opensmile |
     sw-praat | Praat | https://www.fon.hum.uva.nl/praat/ |
     sw-parselmouth | Parselmouth | https://parselmouth.readthedocs.io/ |
     sw-torchaudio | torchaudio | https://pytorch.org/audio | 2.1
     sw-whisper | OpenAI Whisper (Large) | https://github.com/openai/whisper |

Cleaning Strategies

- ID
    clean-1
  Name
    Data cleaning and packaging
  Description
    - Conversion/merging of source data into phenotype files and spectrogram parquet using b2aiprep
    - Creation of data dictionaries (phenotype.json, static_features.json) describing each column/feature

Labeling Strategies

- ID
    label-1
  Name
    Labeling/transcription
  Description
    - ASR transcriptions generated using Whisper Large; transcripts of free speech were removed prior to release

Raw Sources

- ID
    raw-1
  Name
    Raw data availability
  Description
    - In v1.0, audio waveforms are omitted; only spectrograms and derived features are provided. Raw audio may be considered for future releases with additional safeguards.

External Resources

Archival | External Resources | ID | Name | Restrictions
--- | --- | --- | --- | ---
DOI landing page provides versioned records (v1.0) | https://docs.b2ai-voice.org | ext-docs | Project documentation | Credentialed access with DUA and training required for files
| https://doi.org/10.5281/zenodo.14148755 | ext-redcap | Bridge2AI Voice REDCap (v3.20.0) - Zenodo |
| https://github.com/sensein/b2aiprep | ext-b2aiprep | b2aiprep library (open source) |

Is Deidentified

ID
  deid-1
Name
  De-identification
Description
  - HIPAA Safe Harbor identifiers removed (e.g., names, detailed dates, contact info, SSNs, MRNs, device IDs, URLs, biometric identifiers)
  - State/province removed; country of data collection retained
  - Transcripts of free speech removed
  - Audio waveforms omitted in v1.0; only derived data released

Sensitive Elements

- ID
    sens-1
  Name
    Sensitive data considerations
  Description
    - Contains demographic, clinical, and questionnaire data; released elements considered low risk after de-identification

Maintainers

- ID
    maint-1
  Name
    Hosting and maintenance
  Description
    - Health Data Nexus
    - Temerty Centre for AI Research and Education in Medicine (Supported by the Temerty Foundation)

Errata
Is Tabular
Mixed (Parquet, TSV, JSON)
Subsets

Description | Dialect | Encoding | Format | ID | Is Data Split | Is Subpopulation | Media Type | Name | Path | Title
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
Parquet file storing dense time-frequency representations derived from raw audio waveforms with part... |  | UTF-8 |  | subset-spectrograms-parquet | False | Adult cohort (v1.0 only) | application/x-parquet | spectrograms.parquet | spectrograms.parquet | Spectrograms derived from raw audio
Tab-delimited file containing demographics, acoustic confounders, and responses to validated questio... | delimiter: header: True | UTF-8 |  | subset-phenotype-tsv | False | Adult cohort (v1.0 only) | text/tab-separated-values | phenotype.tsv | phenotype.tsv | Phenotype data (participant-level)
JSON data dictionary detailing each phenotype column and its description. |  | UTF-8 | JSON | subset-phenotype-json | False | Adult cohort (v1.0 only) | application/json | phenotype.json | phenotype.json | Data dictionary for phenotype data
Tab-delimited file with one row per recording; includes features from openSMILE, Praat, parselmouth,... | delimiter: header: True | UTF-8 |  | subset-static-features-tsv | False | Adult cohort (v1.0 only) | text/tab-separated-values | static_features.tsv | static_features.tsv | Static audio features
JSON data dictionary describing each feature present in static_features.tsv. |  | UTF-8 | JSON | subset-static-features-json | False | Adult cohort (v1.0 only) | application/json | static_features.json | static_features.json | Data dictionary for static features

🚀

## Uses

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

Tasks

1. ID
     task-1
   Name
     Clinical voice AI tasks
   Description
     Model development and evaluation for condition detection/monitoring from voice-derived signals.
   Response
     Disease screening, detection, and monitoring tasks related to voice disorders, neurological/neurodegenerative disorders, mood/psychiatric disorders, and respiratory disorders.

License And Use Terms

ID
  terms-1
Name
  License and access terms
Description
  - License
      Bridge2AI Voice Registered Access License
  - Data Use Agreement
      Bridge2AI Voice Registered Access Agreement
  - Access Policy
      Only credentialed users who sign the DUA can access the files
  - Required Training
      TCPS 2: CORE 2022

Future Use Impacts

- ID
    impact-1
  Name
    Considerations for future use
  Description
    - v1.0 excludes raw audio and free speech transcripts, which may limit certain modeling approaches (e.g., end-to-end raw waveform models)
    - Adult-only cohort and targeted clinical groups may affect generalizability to pediatric populations and to conditions outside the five categories
    - Planned inclusion of raw audio in future releases will require continued attention to privacy and security safeguards

Discouraged Uses
📤

## Distribution

How will the dataset be distributed?

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

ID
  versions-1
Name
  Versioning and access
Description
  - DOI (version 1.0)
      https://doi.org/10.57764/qb6h-em84
  - DOI (latest Version)
      https://doi.org/10.57764/3sg0-7440

🔄

## Maintenance

How will the dataset be maintained?

Version
1.0
Updates

ID
  updates-1
Name
  Update plan
Description
  - Future releases aim to include original voice data with additional security precautions; pediatric cohort planned for future inclusion

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