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Stud Health Technol Inform ; 216: 1047, 2015.
Article in English | MEDLINE | ID: mdl-26262346

ABSTRACT

This paper deals with the discrimination between healthy and pathological speech signals using recurrence plots and wavelet transform with texture features. Approximation and detail coefficients are obtained from the recurrence plots using Haar wavelet transform, considering one decomposition level. The considered laryngeal pathologies are: paralysis, Reinke's edema and nodules. Accuracy rates above 86% were obtained by means of the employed method.


Subject(s)
Diagnosis, Computer-Assisted/methods , Laryngeal Diseases/diagnosis , Sound Spectrography/methods , Speech Disorders/diagnosis , Speech Disorders/etiology , Speech Production Measurement/methods , Wavelet Analysis , Algorithms , Humans , Laryngeal Diseases/complications , Machine Learning , Pattern Recognition, Automated/methods , Reproducibility of Results , Sensitivity and Specificity
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