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Identification of Pathological Voices Using Glottal Noise Measures

Parsa, Vijay, Jamieson, Donald G.·2000·Journal of Speech, Language, and Hearing Research

Abstract

We investigated the abilities of four fundamental frequency (F 0 )-dependent and two F 0 -independent measures to quantify vocal noise. Two of the F 0 -dependent measures were computed in the time domain, and two were computed using spectral information from the vowel. The F 0 -independent measures were based on the linear prediction (LP) modeling of vowel samples. Tests using a database of sustained vowel samples, collected from 53 normal and 175 pathological talkers, showed that measures based on the LP model were much superior to the other measures. A classification rate of 96.5% was achieved by a parameter that quantifies the spectral flatness of the unmodeled component of the vowel sample.

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Metadata

Authors
Parsa, V., & Jamieson, D. G.
Venue
Journal of Speech, Language, and Hearing Research
Published
2000-04
Volume
43
Issue
2
Pages
469-485
ISSN
  • 1092-4388 (ISSN-L)
  • 1558-9102
OpenAlex
W2079240096
Cited by
182
References
0
FWCI
1.13
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Identification of Pathological Voices Using Glottal Noise Measures. https://app.cochat.ai/papers/10.1044/jslhr.4302.469
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Parsa, V., & Jamieson, D. G. (2000). Identification of Pathological Voices Using Glottal Noise Measures. Journal of Speech, Language, and Hearing Research. https://doi.org/10.1044/jslhr.4302.469

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.