Detection of pathological diseases using a parametric model of vocal folds and neural networks

P. Chytil, C. Jo, K. Drake, D. Graville, M. Wax, M. Pavel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

There are a number of clinical conditions that affect directly or indirectly the function of the vocal folds and thereby the pressure waveforms of elicited sounds. If the relationships between the clinical conditions and the voice quality are sufficiently reliable, it should be possible to detect these diseases or disorders. The focus of this paper is to determine the set of features and their values that would characterize the speaker’s state of vocal folds. To the extent that these features can capture the anatomical, physiological, and neurological aspects of the speaker they can be potentially used to mediate an unobtrusive approach to diagnosis. We will show a new approach to this problem, supported with results obtained from two disordered voice corpora.

Original languageEnglish (US)
Title of host publication5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2007
PublisherFirenze University Press
Pages71-74
Number of pages4
ISBN (Electronic)9788884536747
StatePublished - Jan 1 2007
Event5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2007 - Florence, Italy
Duration: Dec 13 2007Dec 15 2007

Publication series

Name5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2007

Conference

Conference5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2007
CountryItaly
CityFlorence
Period12/13/0712/15/07

Keywords

  • Glottal pulse
  • Model
  • Pathological voice

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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    Chytil, P., Jo, C., Drake, K., Graville, D., Wax, M., & Pavel, M. (2007). Detection of pathological diseases using a parametric model of vocal folds and neural networks. In 5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2007 (pp. 71-74). (5th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2007). Firenze University Press.