Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.

Journal: Journal of voice : official journal of the Voice Foundation
Published Date: May 1, 2017

Abstract

OBJECTIVES: Speech signal processing techniques have provided several contributions to pathologic voice identification, in which healthy and unhealthy voice samples are evaluated. A less common approach is to identify laryngeal pathologies, for which the use of a noninvasive method for pathologic voice identification is an important step forward for preliminary diagnosis. In this study, a hierarchical classifier and a combination of systems are used to improve the accuracy of a three-class identification system (healthy, physiological larynx pathologies, and neuromuscular larynx pathologies).

Authors

  • Hugo Cordeiro
    Department of Electrical Engineering, Faculty of Sciences and Technology of the New University of Lisbon, 2829-516 Caparica, Portugal; Department of Electronics, Telecommunications and Computers, Higher Institute of Engineering of Lisbon, 1959-007 Lisbon, Portugal. Electronic address: hcordeiro@deetc.isel.ipl.pt.
  • José Fonseca
    Department of Electrical Engineering, Faculty of Sciences and Technology of the New University of Lisbon, 2829-516 Caparica, Portugal.
  • Isabel Guimarães
    Department of Speech and Language Therapy, School of Health Sciences at Alcoitão, 2649-506 Alcabideche, Portugal.
  • Carlos Meneses
    Department of Electronics, Telecommunications and Computers, Higher Institute of Engineering of Lisbon, 1959-007 Lisbon, Portugal.

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