Clinical Cutoff Scores for Acoustic Indices of Vocal Hyperfunction That Combine Relative Fundamental Frequency and Cepstral Peak Prominence

Purpose: This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF). Method: Demographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:...

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Published inJournal of speech, language, and hearing research Vol. 65; no. 4; pp. 1349 - 1369
Main Authors Kapsner-Smith, Mara R., Díaz-Cádiz, Manuel E., Vojtech, Jennifer M., Buckley, Daniel P., Mehta, Daryush D., Hillman, Robert E., Tracy, Lauren F., Noordzij, J. Pieter, Eadie, Tanya L., Stepp, Cara E.
Format Journal Article
LanguageEnglish
Published United States American Speech-Language-Hearing Association 01.04.2022
Subjects
Accuracy
Acoustics
Auditory Perception
Care and treatment
Cepstral analysis
Classification
Clinical Diagnosis
Control Groups
Cutting Scores
Demography
Diagnosis
Etiology
Fundamental frequency
Group Membership
Humans
Medical examination
Risk factors
ROC Curve
Speech
Speech Acoustics
Speech Impairments
Throat
Voice
Voice Disorders
Voice Disorders - diagnosis
United States
Online AccessGet full text
ISSN1092-4388
1558-9102
1558-9102
DOI10.1044/2021_JSLHR-21-00466

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Abstract Purpose: This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF). Method: Demographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:1 case-control groups: individuals with and without nonphonotraumatic vocal hyperfunction (NPVH; n = 360) and phonotraumatic vocal hyperfunction (PVH; n = 240). Equations from the final models were used to predict group membership in two independent test sets (n = 100 each). Results: Both CPPS and RFF parameters significantly improved model fits for NPVH and PVH after accounting for demographics. CPPS explained unique variance beyond RFF in both models. RFF explained unique variance beyond CPPS in the PVH model. Final models included CPPS and RFF offset parameters for both NPVH and PVH; RFF onset parameters were significant only in the PVH model. Area under the receiver operating characteristic curve analysis for the independent test sets revealed acceptable classification for NPVH (72%) and good classification for PVH (86%). Conclusions: A combination of CPPS and RFF parameters showed better discriminative ability than either measure alone for PVH. Clinical cutoff scores for acoustic indices of vocal hyperfunction are proposed for assessment and screening purposes.
AbstractList This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF). Demographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:1 case-control groups: individuals with and without nonphonotraumatic vocal hyperfunction (NPVH; = 360) and phonotraumatic vocal hyperfunction (PVH; = 240). Equations from the final models were used to predict group membership in two independent test sets ( = 100 each). Both CPPS and RFF parameters significantly improved model fits for NPVH and PVH after accounting for demographics. CPPS explained unique variance beyond RFF in both models. RFF explained unique variance beyond CPPS in the PVH model. Final models included CPPS and RFF offset parameters for both NPVH and PVH; RFF onset parameters were significant only in the PVH model. Area under the receiver operating characteristic curve analysis for the independent test sets revealed acceptable classification for NPVH (72%) and good classification for PVH (86%). A combination of CPPS and RFF parameters showed better discriminative ability than either measure alone for PVH. Clinical cutoff scores for acoustic indices of vocal hyperfunction are proposed for assessment and screening purposes.
Purpose: This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF). Method: Demographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:1 case-control groups: individuals with and without nonphonotraumatic vocal hyperfunction (NPVH; n = 360) and phonotraumatic vocal hyperfunction (PVH; n = 240). Equations from the final models were used to predict group membership in two independent test sets (n = 100 each). Results: Both CPPS and RFF parameters significantly improved model fits for NPVH and PVH after accounting for demographics. CPPS explained unique variance beyond RFF in both models. RFF explained unique variance beyond CPPS in the PVH model. Final models included CPPS and RFF offset parameters for both NPVH and PVH; RFF onset parameters were significant only in the PVH model. Area under the receiver operating characteristic curve analysis for the independent test sets revealed acceptable classification for NPVH (72%) and good classification for PVH (86%). Conclusions: A combination of CPPS and RFF parameters showed better discriminative ability than either measure alone for PVH. Clinical cutoff scores for acoustic indices of vocal hyperfunction are proposed for assessment and screening purposes.
This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF).PURPOSEThis study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative fundamental frequency (RFF).Demographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:1 case-control groups: individuals with and without nonphonotraumatic vocal hyperfunction (NPVH; n = 360) and phonotraumatic vocal hyperfunction (PVH; n = 240). Equations from the final models were used to predict group membership in two independent test sets (n = 100 each).METHODDemographic, CPPS, and RFF parameters were entered into logistic regression models trained on two 1:1 case-control groups: individuals with and without nonphonotraumatic vocal hyperfunction (NPVH; n = 360) and phonotraumatic vocal hyperfunction (PVH; n = 240). Equations from the final models were used to predict group membership in two independent test sets (n = 100 each).Both CPPS and RFF parameters significantly improved model fits for NPVH and PVH after accounting for demographics. CPPS explained unique variance beyond RFF in both models. RFF explained unique variance beyond CPPS in the PVH model. Final models included CPPS and RFF offset parameters for both NPVH and PVH; RFF onset parameters were significant only in the PVH model. Area under the receiver operating characteristic curve analysis for the independent test sets revealed acceptable classification for NPVH (72%) and good classification for PVH (86%).RESULTSBoth CPPS and RFF parameters significantly improved model fits for NPVH and PVH after accounting for demographics. CPPS explained unique variance beyond RFF in both models. RFF explained unique variance beyond CPPS in the PVH model. Final models included CPPS and RFF offset parameters for both NPVH and PVH; RFF onset parameters were significant only in the PVH model. Area under the receiver operating characteristic curve analysis for the independent test sets revealed acceptable classification for NPVH (72%) and good classification for PVH (86%).A combination of CPPS and RFF parameters showed better discriminative ability than either measure alone for PVH. Clinical cutoff scores for acoustic indices of vocal hyperfunction are proposed for assessment and screening purposes.CONCLUSIONSA combination of CPPS and RFF parameters showed better discriminative ability than either measure alone for PVH. Clinical cutoff scores for acoustic indices of vocal hyperfunction are proposed for assessment and screening purposes.
Audience Professional
Academic
Author Hillman, Robert E.
Kapsner-Smith, Mara R.
Tracy, Lauren F.
Stepp, Cara E.
Vojtech, Jennifer M.
Buckley, Daniel P.
Díaz-Cádiz, Manuel E.
Noordzij, J. Pieter
Mehta, Daryush D.
Eadie, Tanya L.
AuthorAffiliation c Department of Biomedical Engineering, Boston University, MA
g Department of Surgery, Harvard Medical School, Cambridge, MA
e MGH Institute of Health Professions, Boston, MA
d Department of Otolaryngology—Head & Neck Surgery, Boston University School of Medicine, MA
f Center for Laryngeal Surgery and Voice Rehabilitation, Massachusetts General Hospital, Boston
b Department of Speech, Language & Hearing Sciences, Boston University, MA
a Department of Speech & Hearing Sciences, University of Washington, Seattle
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  givenname: J. Pieter
  surname: Noordzij
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  organization: Department of Speech, Language & Hearing Sciences, Boston University, MA, Department of Otolaryngology—Head & Neck Surgery, Boston University School of Medicine, MA
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CitedBy_id crossref_primary_10_1016_j_jvoice_2023_06_004
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crossref_primary_10_3390_app12168121
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Editor: Jack J. Jiang
Disclosure: Jennifer M. Vojtech is currently employed by Delsys, Inc., a commercial company that manufactures and markets sensor and software technologies for human movement, and Altec, Inc., an R&D company that performs research to design new technologies for human movement. Robert E. Hillman and Daryush Mehta have financial interests in InnoVoyce LLC, a company focused on developing and commercializing technologies for the prevention, diagnosis, and treatment of voice-related disorders. Their interests were reviewed and are managed by Massachusetts General Hospital and Mass General Brigham in accordance with their conflict of interest policies. Cara Stepp has received consulting fees from Altec, Inc./Delsys, Inc., companies focused on developing and commercializing technologies related to human movement. C. Stepp's interests were reviewed and are managed by Boston University in accordance with their conflict of interest policies. The other authors have declared that no other competing financial or nonfinancial interests existed at the time of publication.
Editor-in-Chief: Bharath Chandrasekaran
ORCID 0000-0001-7770-6464
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PublicationTitle Journal of speech, language, and hearing research
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Snippet Purpose: This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and...
This study examined the discriminative ability of acoustic indices of vocal hyperfunction combining smoothed cepstral peak prominence (CPPS) and relative...
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SubjectTerms Accuracy
Acoustics
Auditory Perception
Care and treatment
Cepstral analysis
Classification
Clinical Diagnosis
Control Groups
Cutting Scores
Demography
Diagnosis
Etiology
Fundamental frequency
Group Membership
Humans
Medical examination
Risk factors
ROC Curve
Speech
Speech Acoustics
Speech Impairments
Throat
Voice
Voice Disorders
Voice Disorders - diagnosis
Title Clinical Cutoff Scores for Acoustic Indices of Vocal Hyperfunction That Combine Relative Fundamental Frequency and Cepstral Peak Prominence
URI http://eric.ed.gov/ERICWebPortal/detail?accno=EJ1343135
https://www.ncbi.nlm.nih.gov/pubmed/35263546
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