Reinke's Edema and Nodules Identification in Vowels Using Spectral Features and Pitch Jitter

AbstractThe identification of voice pathologies using speech processing techniques can be an useful contribution to the diagnose of larynx diseases. This work presents an identification system using spectral features and pitch jitter extracted from the sustained vowels /a/, /e/ and /i/. A SVM (Support Vector Machine) classifier has been implemented to discriminate Reinke's edema pathologies from nodules. The main objective of this work is to inspect if the spectral features reported in previous work for the vowel /a/ are present in others vowels, and evaluate the voice pathologies identification rate