Abstract
Reverberation is an audio effect used in music production affecting the audio spectrum, as well as the timbre, of music. Technical ear training concerning the ways that reverberation works on music samples is important, since in order to achieve the desired texture sound engineers need to be able to perceive subtle audio changes. However, “dry” recordings, i.e. those that lack reverberation, are not universally available for music production students for the purposes of practice. In this paper, we propose a deep learning-based music dereverberation method to generate de-reverbed music samples for technical ear training in music production education. The experiment results show that based on various objective evaluation metrics, the proposed method can effectively realize dereverberation compared to other neural network-based methods.
Original language | English |
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Number of pages | 21 |
Journal | Asia-Pacific Journal for Arts Education |
Issue number | Special Issue 2023 |
Publication status | Published - 2023 |
Event | International Conference on Music Education Technology 2023 (ICMdT2023): Unfold the Future of Music Education through Technology - Hybrid, Education University of Hong Kong, Hong Kong Duration: 10 Jan 2023 → 12 Jan 2023 https://www.icmdt2023.com/ |
Research Keywords
- (de)reverberation
- audio spectrum
- timbre
- texture
- technical ear training
- music production