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.
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