title: Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.
abstract: OBJECTIVE
  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).
  
  
  METHODS
  Three main subject classes were considered: subjects with physiological larynx pathologies (vocal fold nodules and edemas: 59 samples), subjects with neuromuscular larynx pathologies (unilateral vocal fold paralysis: 59 samples), and healthy subjects (36 samples). The variables used in this study were a speech task (sustained vowel /a/ or continuous reading speech), features with or without perceptual information, and features with or without direct information about formants evaluated using single classifiers. A hierarchical classification system was designed based on this information.
  
  
  RESULTS
  The resulting system combines an analysis of continuous speech by way of the commonly used sustained vowel /a/ to obtain spectral and perceptual speech features. It achieved an accuracy of 84.4%, which represents an improvement of approximately 9% compared with the stand-alone approach. For pathologic voice identification, the accuracy obtained was 98.7%, and the identification accuracy for the two pathology classes was 81.3%.
  
  
  CONCLUSIONS
  Hierarchical classification and system combination create significant benefits and introduce a modular approach to the classification of larynx pathologies.
authors.affiliation: 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.
authors.forename: Hugo
authors.initials: H
authors.lastname: Cordeiro
authors.affiliation: Department of Electrical Engineering, Faculty of Sciences and Technology of the New University of Lisbon, 2829-516 Caparica, Portugal.
authors.forename: José
authors.initials: J
authors.lastname: Fonseca
authors.affiliation: Department of Speech and Language Therapy, School of Health Sciences at Alcoitão, 2649-506 Alcabideche, Portugal.
authors.forename: Isabel
authors.initials: I
authors.lastname: Guimarães
authors.affiliation: Department of Electronics, Telecommunications and Computers, Higher Institute of Engineering of Lisbon, 1959-007 Lisbon, Portugal.
authors.forename: Carlos
authors.initials: C
authors.lastname: Meneses
mesh_terms: D016022:Case-Control Studies; D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004487:Edema / Q000145:classification / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D005260:Female; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D012815:Signal Processing, Computer-Assisted; D013061:Speech Acoustics; D013068:Speech Production Measurement / Q000379:methods*; D060388:Support Vector Machine; D014826:Vocal Cord Paralysis / Q000145:classification / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D014827:Vocal Cords / Q000473:pathology / Q000503:physiopathology; D014832:Voice Disorders / Q000145:classification / Q000175:diagnosis* / Q000473:pathology / Q000503:physiopathology; D014833:Voice Quality
keywords: Continuous speech; Hierarchical classification; Larynx pathology identification; Pathologic voice identification; Sustained vowel