Categorizing normal and pathological voices: automated and perceptual categorization.

  title={Categorizing normal and pathological voices: automated and perceptual categorization.},
  author={Virgilijus Uloza and Antanas Verikas and Marija Bacauskiene and Adas Gelzinis and Ruta Pribuisiene and Marius Kaseta and Viktoras Saferis},
  journal={Journal of voice : official journal of the Voice Foundation},
  volume={25 6},
OBJECTIVES The aims of the present study were to evaluate the accuracy of an elaborated automated voice categorization system that classified voice signal samples into healthy and pathological classes and to compare it with classification accuracy that was attained by human experts. MATERIAL AND METHODS We investigated the effectiveness of 10 different feature sets in the classification of voice recordings of the sustained phonation of the vowel sound /a/ into the healthy and two pathological… CONTINUE READING


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