Artificial Neural Network Based Pathological Voice Classification Using MFCC Features
4 years, 2 months ago
•The analysis of pathological voice is a challenging and an important area of research in speech processing.•It provides a method for the identification and classification of pathological voice using ANN.•Multilayer Perceptron Neural Network (MLPNN), Generalised Regression Neural Network (GRNN) and Probabilistic Neural Network (PNN) methods are used for classifying the pathological voices.
•Mel – Frequency Cepstral Coefficients (MFCC) features extracted from audio recordings are used for this purpose.
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