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: Fifth International Conference on Advances in Bio-Informatics, Bio-Technology and Environmental Engineering - ABBE 2017, 02-03 September, 2017, Zurich, Switzerland.

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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 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

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: 11 Mar 2019 08:32
Last Modified: 11 Mar 2019 08:32
URI: http://publications.theired.org/id/eprint/413

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