Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice

Kitayama, Itsuki; Hosokawa, Kiyohito; Iwaki, Shinobu; Yoshida, Misao; Miyauchi, Akira; Kishikawa, Toshihiro; Tanaka, Hidenori; Tsuda, Takeshi; Sato, Takashi; Takenaka, Yukinori; Ogawa, Makoto; Inohara, Hidenori

doi:https://doi.org/10.1121/10.0034624

Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice

Kitayama, Itsuki; Hosokawa, Kiyohito; Iwaki, Shinobu et al.

Journal of the Acoustical Society of America, 2024, 156(6), 4217-4228

Number of Access:1,583（2025-08-14 00:15 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/100149

Link to primary information

File	Format	Terms of use	Size	Views	Date.Available	Description	information
JAcoustSocAm_156_6_4217	pdf	None	3.41 MB	17	2025.06.24

Item Information

Output File Export EndNote Basic Export Mendeley

Title	Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice
Creator	ORCID 0009-0006-6551-2818 0009-0006-6551-2818 researchmap permalink itkktym itkktym CreatorName Kitayama, Itsuki
	NRID 1000060625896 1000060625896 ORCID 0000-0002-5169-1038 0000-0002-5169-1038 researchmap permalink drink drink Scopus Author ID 55914870000 55914870000 CreatorName Hosokawa, Kiyohito
	CreatorName Iwaki, Shinobu
	CreatorName Yoshida, Misao
	CreatorName Miyauchi, Akira
	NRID 1000020756944 1000020756944 researchmap permalink tk0513 tk0513 CreatorName Kishikawa, Toshihiro
	NRID 1000000804379 1000000804379 ORCID 0000-0002-7516-9180 0000-0002-7516-9180 researchmap permalink hidenoritanaka hidenoritanaka CreatorName Tanaka, Hidenori
	NRID 1000000778631 1000000778631 researchmap permalink gam92471 gam92471 CreatorName Tsuda, Takeshi
	NRID 1000030756002 1000030756002 researchmap permalink 4501 4501 Scopus Author ID 7406982585 7406982585 CreatorName Sato, Takashi
	NRID 1000040598398 1000040598398 ORCID 0000-0002-3135-5635 0000-0002-3135-5635 researchmap permalink yukinoritakenaka yukinoritakenaka Scopus Author ID 7102054128 7102054128 CreatorName Takenaka, Yukinori
	NRID 1000080403179 1000080403179 researchmap permalink mogawa-0731 mogawa-0731 CreatorName Ogawa, Makoto
	NRID 1000000273657 1000000273657 researchmap permalink read0046473 read0046473 Scopus Author ID 7004501837 7004501837 CreatorName Inohara, Hidenori
Description	Kitayama I., Hosokawa K., Iwaki S., et al. Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice. Journal of the Acoustical Society of America 156, 4217 (2024); https://doi.org/10.1121/10.0034624.
Abstract	The fundamental frequency (fo) is pivotal for quantifying vocal-fold characteristics. However, the accuracy of fo estimation in hoarse voices is notably low, and no definitive algorithm for fo estimation has been previously established. In this study, we introduce an algorithm named, “Spectral-based fo Estimator Emphasized by Domination and Sequence (SFEEDS),” which enhances the spectrum method and conducted comparative analyses with conventional estimation methods. We analyzed 454 voice samples and used conventional methods and SFEEDS to calculate fo. The ground truth of fo was determined as the lowest frequency within the most dominant harmonic complex observed on the spectrogram. Subsequently, we assessed the concordance between each fo-estimation method and the fo ground truth. We also examined the variations in the accuracy of these methods when analyzing speech with hoarseness. Regardless of hoarseness, the fo-estimation accuracy was significantly greater by SFEEDS than by conventional methods. Moreover, whereas the conventional methods impaired fo-estimation accuracy in samples with roughness, the SFEEDS algorithm was robust and significantly reduced subharmonic errors. The SFEEDS fo-estimation algorithm accurately estimated the fo of both normal and hoarse voices.
Publisher	Acoustical Society of America
Source Title	Journal of the Acoustical Society of America
Volume (Issue)	156(6)
Page	4217-4228
Date of Issued	2024-12-24
Language	English
Handle URL	https://hdl.handle.net/11094/100149
PISSN	00014966
eISSN	15208524
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.1121/10.0034624
Access Rights	open access
CopyRight	Copyright 2024 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCTERMS.bibliographicCitation	Journal of the Acoustical Society of America. 2024, 156(6), p. 4217-4228
DC.title	Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice
DC.creator	Kitayama, Itsuki
	Hosokawa, Kiyohito
	Iwaki, Shinobu
	Yoshida, Misao
	Miyauchi, Akira
	Kishikawa, Toshihiro
	Tanaka, Hidenori
	Tsuda, Takeshi
	Sato, Takashi
	Takenaka, Yukinori
	Ogawa, Makoto
	Inohara, Hidenori
DC.publisher	Acoustical Society of America
DC.language' scheme='DCTERMS.RFC1766	English
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2024-12-24
DC.identifier	https://doi.org/10.1121/10.0034624
DC.description	Kitayama I., Hosokawa K., Iwaki S., et al. Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice. Journal of the Acoustical Society of America 156, 4217 (2024); https://doi.org/10.1121/10.0034624.
DCTERMS.abstract	The fundamental frequency (fo) is pivotal for quantifying vocal-fold characteristics. However, the accuracy of fo estimation in hoarse voices is notably low, and no definitive algorithm for fo estimation has been previously established. In this study, we introduce an algorithm named, “Spectral-based fo Estimator Emphasized by Domination and Sequence (SFEEDS),” which enhances the spectrum method and conducted comparative analyses with conventional estimation methods. We analyzed 454 voice samples and used conventional methods and SFEEDS to calculate fo. The ground truth of fo was determined as the lowest frequency within the most dominant harmonic complex observed on the spectrogram. Subsequently, we assessed the concordance between each fo-estimation method and the fo ground truth. We also examined the variations in the accuracy of these methods when analyzing speech with hoarseness. Regardless of hoarseness, the fo-estimation accuracy was significantly greater by SFEEDS than by conventional methods. Moreover, whereas the conventional methods impaired fo-estimation accuracy in samples with roughness, the SFEEDS algorithm was robust and significantly reduced subharmonic errors. The SFEEDS fo-estimation algorithm accurately estimated the fo of both normal and hoarse voices.
DC.rights	Copyright 2024 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America.
DC.format	100149
citation_title	Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice
citation_author	Kitayama, Itsuki
	Hosokawa, Kiyohito
	Iwaki, Shinobu
	Yoshida, Misao
	Miyauchi, Akira
	Kishikawa, Toshihiro
	Tanaka, Hidenori
	Tsuda, Takeshi
	Sato, Takashi
	Takenaka, Yukinori
	Ogawa, Makoto
	Inohara, Hidenori
citation_publisher	Acoustical Society of America
citation_language	English
citation_date	2024-12-24
citation_journal_title	Journal of the Acoustical Society of America
citation_volume	156
citation_issue	6
citation_firstpage	4217
citation_lastpage	4228
citation_doi	https://doi.org/10.1121/10.0034624
citation_public_url	https://hdl.handle.net/11094/100149

Robust fundamental frequency-detection algorithm unaffected by the presence of hoarseness in human voice

Link to primary information

Item Information

Show details