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Characterization Methods for the Detection of Multiple Voice Disorders: Neurological, Functional, and Laryngeal Diseases

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F15%3A00233500" target="_blank" >RIV/68407700:21230/15:00233500 - isvavai.cz</a>

  • Result on the web

    <a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7192603" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7192603</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/JBHI.2015.2467375" target="_blank" >10.1109/JBHI.2015.2467375</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Characterization Methods for the Detection of Multiple Voice Disorders: Neurological, Functional, and Laryngeal Diseases

  • Original language description

    This paper evaluates the accuracy of different characterization methods for the automatic detection of multiple speech disorders. The speech impairments considered include dysphonia in people with Parkinson?s disease (PD), dysphonia diagnosed in patientswith different laryngeal pathologies (LP), and hypernasality in children with cleft lip and palate (CLP). Four different methods are applied to analyze the voice signals including noise content measures, spectral-cepstralmodeling, nonlinear features, andmeasurements to quantify the stability of the fundamental frequency. These measures are tested in six databases: three with recordings of PD patients, two with patients with LP, and one with children with CLP. The abnormal vibration of the vocal folds observed in PD patients and in people with LP is modeled using the stability measures with accuracies ranging from 81% to 99% depending on the pathology. The spectral-cepstral features are used in this paper to model the voice spectrum wit

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    JA - Electronics and optoelectronics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GAP102%2F12%2F2230" target="_blank" >GAP102/12/2230: Acoustic voice and speech analysis in patients with central nervous system disorders</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Journal of Biomedical and Health Informatics

  • ISSN

    2168-2194

  • e-ISSN

  • Volume of the periodical

    19

  • Issue of the periodical within the volume

    6

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    9

  • Pages from-to

    1820-1828

  • UT code for WoS article

    000364857000006

  • EID of the result in the Scopus database

    2-s2.0-84959237081