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The amount of digital data is increasing every day. At every step of our daily lives, we deal with technologies in which our data are stored (e.g., mobile phones and laptops), and this is one of the main reasons for the design of various types of encryption and user identity verification algorithms. These algorithms are meant not only to fulfill the desire of protecting data but also to address the possibility of granting access of specific digital data to selected individuals. This process brings with it the problem of identity verification. This paper discusses the problem of voice verification and presents a voice verification method based on artificial intelligence methods. Numerous tests are performed herein to demonstrate the effectiveness of the presented solution. The research results are shown and discussed in terms of the advantages and disadvantages of the solution.


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Voice Recognition by Neuro-Heuristic Method

Show Author's information Dawid Połap( )Marcin Woźniak
Institute of Mathematics, Silesian University of Technology, Kaszubska 23, Poland.

Abstract

The amount of digital data is increasing every day. At every step of our daily lives, we deal with technologies in which our data are stored (e.g., mobile phones and laptops), and this is one of the main reasons for the design of various types of encryption and user identity verification algorithms. These algorithms are meant not only to fulfill the desire of protecting data but also to address the possibility of granting access of specific digital data to selected individuals. This process brings with it the problem of identity verification. This paper discusses the problem of voice verification and presents a voice verification method based on artificial intelligence methods. Numerous tests are performed herein to demonstrate the effectiveness of the presented solution. The research results are shown and discussed in terms of the advantages and disadvantages of the solution.

Keywords: neural network, image processing, heuristic algorithms, Discrete Fourier Transform (DFT)

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Publication history

Received: 30 March 2017
Revised: 21 June 2017
Accepted: 29 June 2017
Published: 08 November 2018
Issue date: February 2019

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© The author(s) 2019

Acknowledgements

Authors acknowledge the contribution to this project from the Diamond Grant 2016 (No. 0080/DIA/2016/45) funded by the Polish Ministry of Science and Higher Education.

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