Voice Identification Using Neural Network And Mel Frequency Cepstrum Coefficients

Abstract

Voice as a communication media for human and computer communication is developed by using voice recognition/identification technology. One of its applications is differentiate between male and female voices. Some speech recognition research have been proposed in disseminating male and female voices, this paper performs male and female voice extraction by using Mel Frequency Cestrum Coefficients (MFCC) as the characteristic vector in back propagation artificial neural network (ANN). The weight change cycle or EPOCH (Exponential Decay) is used to initialize male and female voice identification by using multiple recorded voices. As results, the female voice identification is better than of male with error less than 1.