Texture Analysis of Recurrence Plots Based on Wavelets and PSO for Laryngeal Pathologies Detection.
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.
Academic Unity of Industry, Electrical Engineering, IFPB, João Pessoa, Brazil.
Taciana A
TA
Souza
Electrical Engineering Post-graduation Program, UFCG, Campina Grande, Brazil.
Vinícius J D
VJ
Vieira
Academic Unity of Industry, Electrical Engineering, IFPB, João Pessoa, Brazil.
Suzete E N
SE
Correia
Academic Unity of Industry, Electrical Engineering, IFPB, João Pessoa, Brazil.
Silvana L N C
SL
Costa
Academic Unity of Industry, Electrical Engineering, IFPB, João Pessoa, Brazil.
Washington C
WC
de A Costa
Academic Unity of Industry, Electrical Engineering, IFPB, João Pessoa, Brazil.
Micael A
MA
Souza
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D007818:Laryngeal Diseases / Q000150:complications / Q000175:diagnosis*; D000069550:Machine Learning; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013018:Sound Spectrography / Q000379:methods*; D013064:Speech Disorders / Q000175:diagnosis* / Q000209:etiology*; D013068:Speech Production Measurement / Q000379:methods*; D058067:Wavelet Analysis