Method for Restoring Audio Signal Using Convolutional Neural Networks
https://doi.org/10.25205/1818-7900-2022-20-3-38-50
Abstract
This paper describes a research of the restoring distorted audio signal possibility. Based on the previously obtained results of using deep machine learning methods, the concept of a neural network to correct a distorted audio signal has been developed. On the basis of the originally obtained results, several new neural network architectures were developed, focused on the audio signal restoring. The paper contains descriptions of the developed architectures with a theoretical substantiation of the possibility of their application. The presented architectures were tested to solve the problem of restoring the part of a specifc instrument in a musical composition where it was removed. The results of testing the developed architectures of neural networks are presented in several forms.
About the Authors
K. I. Dementyeva
Novosibirsk State University
Russian Federation
Russian Federation
Kristina I. Dementyeva, Assistant of the Department of Applied Mathematics and Cybernetics, Postgraduate studentNovosibirsk
A. A. Rakitsky
Siberian State University of Telecommunications and Information Sciences; Novosibirsk State University
Russian Federation
Russian Federation
Anton A. Rakitskiy, Candidate of Technical Sciences, Associate Professor of the Department of Applied Mathematics and Cybernetics, Researcher, Senior Researcher
Novosibirsk
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Review
For citations:
Dementyeva K.I., Rakitsky A.A. Method for Restoring Audio Signal Using Convolutional Neural Networks. Vestnik NSU. Series: Information Technologies. 2022;20(3):38-50. (In Russ.) https://doi.org/10.25205/1818-7900-2022-20-3-38-50
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