A multivariate model incorporating subharmonic measurements for evaluating vocal roughness

The assessment of voice quality plays a critical role in the clinical evaluation of hoarseness. However, no study has established a highly accurate method for the auditory-perceptual judgment of vocal roughness, which is one of the major components of hoarseness. In this study, we developed a multivariate acoustic model for quantifying vocal roughness using a tailored fundamental frequency (f<sub>o</sub>) estimation algorithm. The newly devised parameters enabled the classification and quantification of subharmonics, a key component of rough voice. Furthermore, we introduce the acoustic roughness index (ARI), a predictive acoustic model that integrates these parameters with existing acoustic parameters. The ARI demonstrates high diagnostic accuracy and a strong correlation with auditory-perceptual roughness, establishing it as a robust index for the evaluation of vocal roughness.

Authors

Institutions

Publication Details

Journal
npj Digital Medicine
Published
2025-05-20
DOI
https://doi.org/10.1038/s41746-025-01702-2
Citations
5
Primary Topic
Voice and Speech Disorders
Type
article
Field-Weighted Citation Impact
5.82

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A multivariate model incorporating subharmonic measurements for evaluating vocal roughness

Akira Miyauchi, Toshihiro Kishikawa, Kiyohito Hosokawa, Takanari Kawabe et al.
5 citations
npj Digital Medicine
Voice and Speech Disorders
5.82
article

A multivariate model incorporating subharmonic measurements for evaluating vocal roughness

Akira Miyauchi, Toshihiro Kishikawa, Kiyohito Hosokawa, Takanari Kawabe, Shinobu Iwaki, Yukinori Takenaka, Itsuki Kitayama, Hidenori Inohara, Hidenori Tanaka, Takeshi Tsuda, Misao Yoshida, Takashi Sato, Makoto Ogawa, Kenji Aruga
article en
5 citations

Abstract

The assessment of voice quality plays a critical role in the clinical evaluation of hoarseness. However, no study has established a highly accurate method for the auditory-perceptual judgment of vocal roughness, which is one of the major components of hoarseness. In this study, we developed a multivariate acoustic model for quantifying vocal roughness using a tailored fundamental frequency (f<sub>o</sub>) estimation algorithm. The newly devised parameters enabled the classification and quantification of subharmonics, a key component of rough voice. Furthermore, we introduce the acoustic roughness index (ARI), a predictive acoustic model that integrates these parameters with existing acoustic parameters. The ARI demonstrates high diagnostic accuracy and a strong correlation with auditory-perceptual roughness, establishing it as a robust index for the evaluation of vocal roughness.

npj Digital MedicineVol. 8(1)
Osaka City University (JP), Kobe University Hospital (JP), Sakai Municipal Hospital (JP), Kuma Hospital (JP), The University of Osaka (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 4%
Voice and Speech Disorders
5.82
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.