. 2024 Mar;134(3):1333-1339.

doi: 10.1002/lary.31052. Epub 2023 Dec 13.

Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey

Collaborators, Affiliations

Collaborators

Bridge2AI-Voice:
E Bensoussan Yael, Elemento Olivier, Rameau Anaïs, Sigaras Alexandros, Ghosh Satrajit, E Powell Maria, Johnson Alistair, Ravitsky Vardit, Bélisle-Pipon Jean-Christophe, Dorr David, Payne Phillip

Affiliations

¹ University of South Florida Morsani College of Medicine, Tampa, Florida, U.S.A.
² Department of Biology, University of South Florida, Tampa, Florida, U.S.A.
³ USF Health, University of South Florida, Tampa, Florida, U.S.A.
⁴ Department of Otolaryngology, Head and Neck Surgery Weill Cornell Medical College, Ithaca, New York, U.S.A.
⁵ Department of Otolaryngology, Head and Neck Surgery Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A.
⁶ Department of Otolaryngology-Head and Neck Surgery Keck College of Medicine, University of Southern California, Los Angeles, California, U.S.A.
⁷ Department of Otolaryngology, Emory University School of Medicine, Atlanta, Georgia, U.S.A.
⁸ Massachusetts Eye and Ear, Division of Laryngology, Otolaryngology-Head and Neck Surgery Harvard Medical School, Boston, Massachusetts, U.S.A.
⁹ Department of Otolaryngology, Head and Neck Surgery at University of South Florida Morsani College of Medicine, Tampa, Florida, U.S.A.
¹⁰ Department of Otolaryngology, Head and Neck Surgery at Cleveland Clinic, Cleveland, Ohio, U.S.A.
¹¹ Massachusetts Eye and Ear, Otolaryngology-Head and Neck Surgery Harvard Medical School, Boston, Massachusetts, U.S.A.
¹² Mila Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada.
¹³ Division of Laryngology Department of Otolaryngology, Head and Neck Surgery at University of South Florida Morsani College of Medicine, Tampa, Florida, U.S.A.

PMID: 38087983
DOI: 10.1002/lary.31052

Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey

Emily Evangelista et al. Laryngoscope. 2024 Mar.

. 2024 Mar;134(3):1333-1339.

doi: 10.1002/lary.31052. Epub 2023 Dec 13.

Authors

Collaborators

Bridge2AI-Voice:
E Bensoussan Yael, Elemento Olivier, Rameau Anaïs, Sigaras Alexandros, Ghosh Satrajit, E Powell Maria, Johnson Alistair, Ravitsky Vardit, Bélisle-Pipon Jean-Christophe, Dorr David, Payne Phillip

Affiliations

¹ University of South Florida Morsani College of Medicine, Tampa, Florida, U.S.A.
² Department of Biology, University of South Florida, Tampa, Florida, U.S.A.
³ USF Health, University of South Florida, Tampa, Florida, U.S.A.
⁴ Department of Otolaryngology, Head and Neck Surgery Weill Cornell Medical College, Ithaca, New York, U.S.A.
⁵ Department of Otolaryngology, Head and Neck Surgery Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A.
⁶ Department of Otolaryngology-Head and Neck Surgery Keck College of Medicine, University of Southern California, Los Angeles, California, U.S.A.
⁷ Department of Otolaryngology, Emory University School of Medicine, Atlanta, Georgia, U.S.A.
⁸ Massachusetts Eye and Ear, Division of Laryngology, Otolaryngology-Head and Neck Surgery Harvard Medical School, Boston, Massachusetts, U.S.A.
⁹ Department of Otolaryngology, Head and Neck Surgery at University of South Florida Morsani College of Medicine, Tampa, Florida, U.S.A.
¹⁰ Department of Otolaryngology, Head and Neck Surgery at Cleveland Clinic, Cleveland, Ohio, U.S.A.
¹¹ Massachusetts Eye and Ear, Otolaryngology-Head and Neck Surgery Harvard Medical School, Boston, Massachusetts, U.S.A.
¹² Mila Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada.
¹³ Division of Laryngology Department of Otolaryngology, Head and Neck Surgery at University of South Florida Morsani College of Medicine, Tampa, Florida, U.S.A.

PMID: 38087983
DOI: 10.1002/lary.31052

Abstract

Introduction: Accuracy and validity of voice AI algorithms rely on substantial quality voice data. Although commensurable amounts of voice data are captured daily in voice centers across North America, there is no standardized protocol for acoustic data management, which limits the usability of these datasets for voice artificial intelligence (AI) research.

Objective: The aim was to capture current practices of voice data collection, storage, analysis, and perceived limitations to collaborative voice research.

Methods: A 30-question online survey was developed with expert guidance from the voicecollab.ai members, an international collaborative of voice AI researchers. The survey was disseminated via REDCap to an estimated 200 practitioners at North American voice centers. Survey questions assessed respondents' current practices in terms of acoustic data collection, storage, and retrieval as well as limitations to collaborative voice research.

Results: Seventy-two respondents completed the survey of which 81.7% were laryngologists and 18.3% were speech language pathologists (SLPs). Eighteen percent of respondents reported seeing 40%-60% and 55% reported seeing >60 patients with voice disorders weekly (conservative estimate of over 4000 patients/week). Only 28% of respondents reported utilizing standardized protocols for collection and storage of acoustic data. Although, 87% of respondents conduct voice research, only 38% of respondents report doing so on a multi-institutional level. Perceived limitations to conducting collaborative voice research include lack of standardized methodology for collection (30%) and lack of human resources to prepare and label voice data adequately (55%).

Conclusion: To conduct large-scale multi-institutional voice research with AI, there is a pertinent need for standardization of acoustic data management, as well as an infrastructure for secure and efficient data sharing.

Level of evidence: 5 Laryngoscope, 134:1333-1339, 2024.

Keywords: artificial intelligence; current practices; data collection; voice.

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References

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Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey

Collaborators

Affiliations

Current Practices in Voice Data Collection and Limitations to Voice AI Research: A National Survey

Authors

Collaborators

Affiliations

Abstract

References

BIBLIOGRAPHY

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Research Materials