Information Redundancy in Constructing Systems for Audio Signal Examination on Deep Learning Neural Networks

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Information Redundancy in Constructing Systems for Audio Signal Examination on Deep Learning Neural Networks

Solovyov, V. I.; Rybalskiy, O. V.; Zhuravel, V. V.; Shablya, A. N.; Tymko, E. V.

Cybernetics and systems analysis, 2022/1, Volume: 58, Issue: 1

Journal Article

Preliminary signal processing methods used to create new tools to examine materials and digital sound recording means are described. It is shown that using information redundancy when creating a training base for deep learning neural networks used for such examination increases speaker identification efficiency based on voice characteristic parameters by about 15%. It is shown that the proposed processing methods enable speaker identification based on phonograms that are 1 second long.

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Solovyov, V. I. | Rybalskiy, O. V. | Zhuravel, V. V. | Shablya, A. N. | Tymko, E. V.

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