Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter

Hugo Tito Cordeiro; José Manuel Matos Ribeiro da Fonseca; Carlos Meneses Ribeiro

doi:10.1016/j.protcy.2014.10.229

Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter

Hugo Tito Cordeiro, José Manuel Matos Ribeiro da Fonseca, Carlos Meneses Ribeiro

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The identification of voice pathologies using speech processing techniques can be an useful contribution to the diagnose of larynx diseases. This work presents an identification system using spectral features and pitch jitter extracted from the sustained vowels /a/, /e/ and /i/. A SVM (Support Vector Machine) classifier has been implemented to discriminate Reinke's edema pathologies from nodules. The main objective of this work is to inspect if the spectral features reported in previous work for the vowel /a/ are present in others vowels, and evaluate the voice pathologies identification rate.

Original language	English
Title of host publication	CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013
Editors	Alessandro Fantoni, Artur J. Ferreira
Place of Publication	Amsterdam
Publisher	ELSEVIER SCIENCE BV
Pages	202–208
DOIs	https://doi.org/10.1016/j.protcy.2014.10.229
Publication status	Published - 2014
Event	2nd Conference on Electronics, Telecommunications, and Computers (CETC) - Lisbon, Portugal Duration: 5 Dec 2013 → 6 Dec 2013 Conference number: 2nd

Publication series

Name	Procedia Technology
Publisher	ELSEVIER SCIENCE BV
Volume	17
ISSN (Print)	2212-0173

Conference

Conference	2nd Conference on Electronics, Telecommunications, and Computers (CETC)
Abbreviated title	CETC
Country	Portugal
City	Lisbon
Period	5/12/13 → 6/12/13

Keywords

Voice pathologies identification
formant frequency
formant bandwidth
pitch jitter
pitch

Access to Document

10.1016/j.protcy.2014.10.229

Fingerprint Dive into the research topics of 'Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter'. Together they form a unique fingerprint.

Cite this

Cordeiro, H. T., Fonseca, J. M. M. R. D., & Ribeiro, C. M. (2014). Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter. In A. Fantoni, & A. J. Ferreira (Eds.), CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013 (pp. 202–208). (Procedia Technology; Vol. 17). ELSEVIER SCIENCE BV. https://doi.org/10.1016/j.protcy.2014.10.229

Cordeiro, Hugo Tito ; Fonseca, José Manuel Matos Ribeiro da ; Ribeiro, Carlos Meneses. / Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter. CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013. editor / Alessandro Fantoni ; Artur J. Ferreira. Amsterdam : ELSEVIER SCIENCE BV, 2014. pp. 202–208 (Procedia Technology).

@inproceedings{0cea9dbd6d95493885e11a0f06461766,

title = "Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter",

abstract = "The identification of voice pathologies using speech processing techniques can be an useful contribution to the diagnose of larynx diseases. This work presents an identification system using spectral features and pitch jitter extracted from the sustained vowels /a/, /e/ and /i/. A SVM (Support Vector Machine) classifier has been implemented to discriminate Reinke's edema pathologies from nodules. The main objective of this work is to inspect if the spectral features reported in previous work for the vowel /a/ are present in others vowels, and evaluate the voice pathologies identification rate.",

keywords = "formant frequency, Voice pathologies identification, pitch, formant bandwidth, pitch jitter, Voice pathologies identification, formant frequency, formant bandwidth, pitch jitter, pitch",

author = "Cordeiro, {Hugo Tito} and Fonseca, {Jos{\'e} Manuel Matos Ribeiro da} and Ribeiro, {Carlos Meneses}",

note = "WOS:000359949800020; 2nd Conference on Electronics, Telecommunications, and Computers (CETC), CETC ; Conference date: 05-12-2013 Through 06-12-2013",

year = "2014",

doi = "10.1016/j.protcy.2014.10.229",

language = "English",

series = "Procedia Technology",

publisher = "ELSEVIER SCIENCE BV",

pages = "202–208",

editor = "Fantoni, {Alessandro } and Ferreira, {Artur J. }",

booktitle = "CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013",

}

Cordeiro, HT, Fonseca, JMMRD & Ribeiro, CM 2014, Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter. in A Fantoni & AJ Ferreira (eds), CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013. Procedia Technology, vol. 17, ELSEVIER SCIENCE BV, Amsterdam, pp. 202–208, 2nd Conference on Electronics, Telecommunications, and Computers (CETC), Lisbon, Portugal, 5/12/13. https://doi.org/10.1016/j.protcy.2014.10.229

Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter. / Cordeiro, Hugo Tito; Fonseca, José Manuel Matos Ribeiro da; Ribeiro, Carlos Meneses.

CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013. ed. / Alessandro Fantoni; Artur J. Ferreira. Amsterdam : ELSEVIER SCIENCE BV, 2014. p. 202–208 (Procedia Technology; Vol. 17).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter

AU - Cordeiro, Hugo Tito

AU - Fonseca, José Manuel Matos Ribeiro da

AU - Ribeiro, Carlos Meneses

N1 - Conference code: 2nd

PY - 2014

Y1 - 2014

N2 - The identification of voice pathologies using speech processing techniques can be an useful contribution to the diagnose of larynx diseases. This work presents an identification system using spectral features and pitch jitter extracted from the sustained vowels /a/, /e/ and /i/. A SVM (Support Vector Machine) classifier has been implemented to discriminate Reinke's edema pathologies from nodules. The main objective of this work is to inspect if the spectral features reported in previous work for the vowel /a/ are present in others vowels, and evaluate the voice pathologies identification rate.

AB - The identification of voice pathologies using speech processing techniques can be an useful contribution to the diagnose of larynx diseases. This work presents an identification system using spectral features and pitch jitter extracted from the sustained vowels /a/, /e/ and /i/. A SVM (Support Vector Machine) classifier has been implemented to discriminate Reinke's edema pathologies from nodules. The main objective of this work is to inspect if the spectral features reported in previous work for the vowel /a/ are present in others vowels, and evaluate the voice pathologies identification rate.

KW - formant frequency

KW - Voice pathologies identification

KW - pitch

KW - formant bandwidth

KW - pitch jitter

KW - Voice pathologies identification

KW - formant frequency

KW - formant bandwidth

KW - pitch jitter

KW - pitch

U2 - 10.1016/j.protcy.2014.10.229

DO - 10.1016/j.protcy.2014.10.229

M3 - Conference contribution

T3 - Procedia Technology

SP - 202

EP - 208

BT - CONFERENCE ON ELECTRONICS, TELECOMMUNICATIONS AND COMPUTERS - CETC 2013

A2 - Fantoni, Alessandro

A2 - Ferreira, Artur J.

PB - ELSEVIER SCIENCE BV

CY - Amsterdam

T2 - 2nd Conference on Electronics, Telecommunications, and Computers (CETC)

Y2 - 5 December 2013 through 6 December 2013

ER -