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Proceedings Paper

Research of neural network classifier in speaker recognition module for automated system of critical use
Author(s): Mykola M. Bykov; Viacheslav V. Kovtun; Andrzej Smolarz; Mukhtar Junisbekov; Aliya Targeusizova; Maksabek Satymbekov
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Paper Abstract

The article studies the dependence of the quality of speakers recognition by convolutional neural network from the type of chosen informative features for use it in automated systems for critical use especially when they are used in the environmental influences. The environmental influences are the noise of high level with a spectrum that correlates with the spectrum of the speech signal or the signal of speaker simulator. –°onvolutional network operation principles for the case of speaker signal recognition, as well as experiments on neural network training and the recognition of speakers on a test samples have been considered. According to the research, it was concluded that the bark-cepstral coefficients make it possible to perform recognition with greater reliability than the spectral parameters of the signal.

Paper Details

Date Published: 7 August 2017
PDF: 7 pages
Proc. SPIE 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017, 1044521 (7 August 2017); doi: 10.1117/12.2280930
Show Author Affiliations
Mykola M. Bykov, Vinnytsia National Technical Univ. (Ukraine)
Viacheslav V. Kovtun, Vinnytsia National Technical Univ. (Ukraine)
Andrzej Smolarz, Lublin Univ. of Technology (Poland)
Mukhtar Junisbekov, M.Kh. Dulaty Taraz State Univ. (Kazakhstan)
Aliya Targeusizova, Al-Farabi Kazakh National Univ. (Kazakhstan)
Maksabek Satymbekov, Institute of Information and Computational Technologies (Kazakhstan)

Published in SPIE Proceedings Vol. 10445:
Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017
Ryszard S. Romaniuk; Maciej Linczuk, Editor(s)

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