Performance Evaluation of Machine Learning Algorithm Applied to a Biometric Voice Recognition System

ANDREA, L PIRODDI (2017) Performance Evaluation of Machine Learning Algorithm Applied to a Biometric Voice Recognition System. In: Sixth International Conference on Advances in Civil, Structural and Environmental Engineering - ACSEE 2017, 09-10 December, 2017, Rome, Italy.

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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 input 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 this particular application.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Biometric, Mel-Frequency Cepstrum Coefficients (MFCC), Voice Recognition, Weka, Open smile, Praat
Depositing User: Mr. John Steve
Date Deposited: 10 Mar 2019 09:23
Last Modified: 10 Mar 2019 09:23
URI: http://publications.theired.org/id/eprint/268

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