Development and Research of Neural Network Based Method for Reconstructing Audio Signals

Kristina Morozova, Anton Rakitskiy

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

In this paper we investigate the possibility of using neural networks to solve the problem of restoring audio signal. Based on the previously obtained results of the convolutional neural networks application for the extraction of a vocal part, we developed the concept of a convolutional neural network designed to correct distorted audio signal. The paper presents the initial concept of this neural network architecture which, unfortunately, showed unsatisfactory results. Nevertheless, based on the concept of this network, several new neural network architectures were developed specifically focused on recovering a distorted audio signal but the shortcomings of the basic architecture were taken into account. The paper contains descriptions of all these architectures and the results of their application to restore the drummer's part in the musical composition where it was removed. The obtained results show the high potential of convolutional neural networks application for solving such a complex problem as audio signal restoration.

Язык оригиналаанглийский
Название основной публикацииProceedings - 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2021
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы316-318
Число страниц3
ISBN (электронное издание)9781728176918
DOI
СостояниеОпубликовано - 13 мая 2021
Событие2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2021 - Yekaterinburg, Российская Федерация
Продолжительность: 13 мая 202114 мая 2021

Серия публикаций

НазваниеProceedings - 2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2021

Конференция

Конференция2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2021
СтранаРоссийская Федерация
ГородYekaterinburg
Период13.05.202114.05.2021

Предметные области OECD FOS+WOS

  • 1.02 КОМПЬЮТЕРНЫЕ И ИНФОРМАЦИОННЫЕ НАУКИ
  • 2.06.IG ИНЖЕНЕРИЯ, БИОМЕДИЦИНСКАЯ
  • 2.02.IQ ИНЖЕНЕРИЯ, ЭЛЕКТРИЧЕСКАЯ И ЭЛЕКТРОННАЯ

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