Neural Models for Target-Based Computer-Assisted Musical Orchestration: A Preliminary Study – ScienceOpen
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      Neural Models for Target-Based Computer-Assisted Musical Orchestration: A Preliminary Study

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          Abstract

          In this paper we will perform a preliminary exploration on how neural networks can be used for the task of target-based computer-assisted musical orchestration. We will show how it is possible to model this  musical problem as a classification task and we will propose two deep learning models. We will show, first, how they perform as classifiers for musical instrument recognition by comparing them with specific baselines. We will then show how they perform, both qualitatively and quantitatively, in the task of computer-assisted orchestration by comparing them with state-of-the-art systems. Finally, we will highlight benefits and problems of neural approaches for assisted orchestration and we will propose possible future steps. This paper is an extended version of the paper "A Study on Neural Models for Target-Based Computer-Assisted Musical Orchestration" published in the proceedings of The 2020 Joint Conference on AI Music Creativity. 

          Author and article information

          Journal
          Journal of Creative Music Systems
          University of Huddersfield Press
          2399-7656
          October 16 2022
          August 30 2022
          : 1
          : 1
          Affiliations
          [1 ]University of California, Berkeley Center for New Music and Audio Technologies
          [2 ]University of California, Berkeley
          [3 ]University of Paris-Saclay Centrale Supélec, L2S
          Article
          10.5920/jcms.890
          7c1f7ecd-ee38-4988-a2ea-670b2072aa25
          © 2022

          https://creativecommons.org/licenses/by/4.0

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