Deep Neural Networks with Music Dereverberation for Technical Ear Training in Music Production Education

Manni Chen*, PerMagnus Lindborg, Shuo Meng

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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 languageEnglish
Number of pages21
JournalAsia-Pacific Journal for Arts Education
Issue numberSpecial Issue 2023
Publication statusPublished - 2023
EventInternational 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 202312 Jan 2023
https://www.icmdt2023.com/

Research Keywords

  • (de)reverberation
  • audio spectrum
  • timbre
  • texture
  • technical ear training
  • music production

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