Abstract: “The article investigates the possibilities of applying machine learning algorithm to identify an individual through biometric voice recognition with the higher possible reliability . The emphasis in the analysis is placed on the possibility of using artificial intelligence approach methods for the purposes of recognizing a person unambiguously, uniquely on the basis of the data contained in his /her vocal spectral information . A large number of routes we can go to parametrically representing the speech signal for the voice recognition system such as Mel - Frequency Cepstrum Coefficients (MFCC). During the authentication phase the in put voice signal is recorded and processed comparing it by using MFCC features with a signal that has been previously stored in the database by the same user. The main purpose is to compare some of the main machine learning algorithms to classify them on t his particular application”

Keywords: Biometric, Mel-Frequency Cepstrum Coefficients (MFCC), Voice Recognition, Weka, Open smile, Praat