The multi-scale product's effect on the recognition of pathological voices

This paper's goal is to look into new criteria for categorizing organic, neurologic, and functional disorders. Mel Frequency Cepstral Coefficients (MFCC) are calculated within the speech multi-scale product (MP). In this study, the pathological voices in the MEEI database were classified using the Support Vector Machine classifier, or SVM. According to the experimental results, classification rates that are acquired using MFCC features that are retrieved from the multi-scale product is more effective than those obtained from the speech signal.