Ideary: Facilitating Electronic Music Creation with Generative AI
Open accessAbstract
This project explores how generative AI can assist electronic music producers in composing rhythms and melodies. Based on detailed user research with electronic music producers, a central tension in music composition is between authorial control and unpredictability. This paper presents Ideary, a concept where users explore the latent space of their custom generative AI models through an XY pad based on extensive user research. A user evaluation shows that music producers responded positively to this approach.
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AI systems can function effectively as brainstorming aids, offering a seemingly endless array of possibilities.
“As multiple studies have noted, AI systems can function effectively as brainstorming aids [45,67,82], offering a seemingly endless array of possibilities.”
From Exploring the Collaborative Co-Creation Process with AI: A Case Study in Novice Music Production (2025) · cites this paper as [45]
The Preliminary Evaluation reports that producers believed Ideary could help them generate ideas and explore unexpected patterns, and the feature description proposes many variations to stimulate creativity. But Ideary was only a clickable design concept, not functioning software, so the paper does not establish that it functioned effectively as a brainstorming aid; it also does not substantiate a seemingly endless range of possibilities. (LLM, conf=0.85)
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Cites
Designing for Playfulness in Human-AI Authoring Tools
Liapis, A., Guckelsberger, C., Zhu, J., Harteveld, C., Kriglstein, S., Denisova, A., Gow, J., & Preuss, M. (2023) · Proceedings of the 18th International Conference on the Foundations of Digital Games · doi:10.1145/3582437.3587192 · Cited by 14 · see citing works
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Flagged first, then by citations
Research works printed but not linked: 6
- Emmanuel Deruty, Maarten Grachten, Stefan Lattner, Javier Nistal, and Cyran Aouameur. 2022. On the development and practice of ai technology for contem- porary popular music production. Transactions of the International Society for Music Information Retrieval 5, 1 (2022).
- Imke Grabe, Miguel Gonzalez Duque, and Jichen Zhu. 2022. Towards a framework for human-ai interaction patterns in co-creative gan applications. In Proceeding of the 3rd Workshop on Human-AI Co-Creation with Generative Models (HAI-GEN '22) at ACM IUI Workshops.
- Imke Grabe and Jichen Zhu. 2023. Hidden Layer Interaction: A Co-Creative Design Fiction for Generative Models. arXiv:2304.00266 (2023). · arXiv
- Nao Tokui. 2020. Can GAN originate new electronic dance music genres?- Generating novel rhythm patterns using GAN with Genre Ambiguity Loss. arXiv preprint arXiv:2011.13062 (2020). · arXiv
- Nao Tokui. 2020. Towards democratizing music production with AI-design of variational autoencoder-based rhythm generator as a DAW plugin. arXiv preprint arXiv:2004.01525 (2020). · arXiv
- Haohang Zhang, Letian Xie, and Kaiyi Qi. 2021. Implement music generation with gan: A systematic review. In 2021 International Conference on Computer Engineering and Application (ICCEA). IEEE, 352-355.
Cited by
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Exploring the Collaborative Co-Creation Process with AI: A Case Study in Novice Music Production
Fu, Y., Newman, M., Going, L., Feng, Q., & Lee, J. H. (2025) · Proceedings of the 2025 ACM Designing Interactive Systems Conference · doi:10.1145/3715336.3735829 · Cited by 30 · see citing works
Exploring the Collaborative Co-Creation Process with AI: A Case Study in Novice Music Production
Fu, Y., Newman, M., Going, L., Feng, Q., & Lee, J. H. (2025) · arXiv · Cited by 30 · see citing works
- Authors
- Larsen, A. H., & Zhu, J.
- Affiliations
- IT University of Copenhagen, Denmark
- IT University of Copenhagen (DK)
- Venue
- Designing Interactive Systems Conference
- Publisher
- ACM
- Published
- 2024-07
- Pages
- 275-278
- OpenAlex
- W4400207164
- Cited by
- 5
- References
- 1
- Citations by year
- 2026: 2 · 2025: 3
- FWCI
- 1.04
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Designing Interactive Systems Conference (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Music Technology and Sound Studies
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Keywords
- generative AI, electronic music production, music composition, rhythm generation, melody generation, authorial control, unpredictability, latent space exploration
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