Publisher DOI: | 10.1186/s13636-022-00266-3 |
Title: | Automatic music signal mixing system based on one-dimensional Wave-U-Net autoencoders |
Language: | English |
Authors: | Koszewski, Damian Görne, Thomas Korvel, Grazina Kostek, Bozena |
Keywords: | Automatic music mixing; Listening tests; Music signal parameterization; Similarity matrix; Wave-U-Net autoencoder |
Issue Date: | 5-Jan-2023 |
Publisher: | Springer |
Journal or Series Name: | EURASIP Journal on audio, speech, and music processing |
Volume: | 2023 |
Abstract: | The purpose of this paper is to show a music mixing system that is capable of automatically mixing separate raw recordings with good quality regardless of the music genre. This work recalls selected methods for automatic audio mixing first. Then, a novel deep model based on one-dimensional Wave-U-Net autoencoders is proposed for automatic music mixing. The model is trained on a custom-prepared dat... |
URI: | http://hdl.handle.net/20.500.12738/13883 |
ISSN: | 1687-4722 |
Review status: | This version was peer reviewed (peer review) |
Institute: | Department Medientechnik Fakultät Design, Medien und Information |
Type: | Article |
Additional note: | article number: 1 (2023) |
Appears in Collections: | Publications without full text |
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