ORIGINAL RESEARCH article
Front. Comput. Sci.
Sec. Human-Media Interaction
Volume 7 - 2025 | doi: 10.3389/fcomp.2025.1597806
This article is part of the Research TopicEmbodied Perspectives on Sound and Music AIView all 11 articles
Approaches to Notation for Embodied Engagement with a Novel Neural Network-Based Musical Instrument
Provisionally accepted
- 1Technical University of Berlin, Berlin, Germany
- 2Hasso Plattner Institut, Potsdam, Brandenburg, Germany
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
The growing complexity and breadth of sonic possibilities enabled by sound synthesis technologies give rise to significant challenges for the notation of music, especially in light of emerging neural network-based paradigms. Prescriptive vs. descriptive notation has emerged as a paradigm with relevance to this challenge. Experienced musicians (n = 11) were asked to compose for a novel neural network-based digital musical instrument and were prompted to produce descriptive and prescriptive graphic notations. Group differences in task conceptualisation were observed, while further analysis revealed perpendicular dimensions of variation in the resulting musical notation, which were associated with perceived creativity support. Based on this analysis, a conceptual framework is proposed that suggests useful strategies for music composition and creative endeavours. One Sentence Summary: Beyond the representation of sound and/or action, use of abstraction and metaphor emerge as strategies for music notation, with consequences for support of creative work.
Keywords: music notation, Digital musical instruments, DMI, prescriptive notation, descriptive notation, Neural Network, embodied music cognition
Received: 21 Mar 2025; Accepted: 04 Sep 2025.
Copyright: © 2025 Bacon, Auri and McKee. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Benjamin Keith Bacon, Technical University of Berlin, Berlin, Germany
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.