Voice data mining for laryngeal pathology assessment
We examined pathological changes in the speech signal of vowels /a/, /i/ and /u/. Various methods of voice signal analysis were examined to detect voice pathologies. Selected features have the influence on detection accuracies of pathological voice. 100% voice pathology detection is achievable using Random Forest algorithm.
voice pathology detection random forest feature selection pca kpca acoustic analysis