MAICO: A Visualization Design Study on AI-Assisted Music Composition

We contribute a design study on using visual analytics for AI-assisted music composition. The main result is the interface MAICO (Music AI Co-creativity), which allows composers and other music creators to interactively generate, explore, select, edit, and compare samples from generative music models. MAICO is based on the idea of visual parameter space analysis and supports the simultaneous analysis of hundreds of short samples of symbolic music from multiple models, displaying them in different metric- and similarity-based layouts. We developed and evaluated MAICO together with a professional composer who actively used it for five months to create, among other things, a composition for the Biennale Arte 2024 in Venice, which was recorded by the Munich Symphonic Orchestra. We discuss our design choices and lessons learned from this endeavor to support Human-AI co-creativity with visual analytics.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-02-07
DOI
https://doi.org/10.1109/tvcg.2025.3539779
Citations
3
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
3.83
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MAICO: A Visualization Design Study on AI-Assisted Music Composition

Simeon Rau, Frank Heyen, Michael Sedlmair, Benedikt Brachtel
3 citations
IEEE Transactions on Visualization and Computer Graphics
Music Technology and Sound Studies
3.83
article

MAICO: A Visualization Design Study on AI-Assisted Music Composition

Simeon Rau, Frank Heyen, Michael Sedlmair, Benedikt Brachtel
article en
3 citations

Abstract

We contribute a design study on using visual analytics for AI-assisted music composition. The main result is the interface MAICO (Music AI Co-creativity), which allows composers and other music creators to interactively generate, explore, select, edit, and compare samples from generative music models. MAICO is based on the idea of visual parameter space analysis and supports the simultaneous analysis of hundreds of short samples of symbolic music from multiple models, displaying them in different metric- and similarity-based layouts. We developed and evaluated MAICO together with a professional composer who actively used it for five months to create, among other things, a composition for the Biennale Arte 2024 in Venice, which was recorded by the Munich Symphonic Orchestra. We discuss our design choices and lessons learned from this endeavor to support Human-AI co-creativity with visual analytics.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(7)
University of Stuttgart (DE), Sonneberg Observatory (DE)
Openalex Percentile: Top 8%
Music Technology and Sound Studies
3.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

MAICO: A Visualization Design Study on AI-Assisted Music Composition — Simeon Rau, Frank Heyen, et al. · IEEE Transactions on Visualization and Computer Graphics (2025) | TGRS Research Map | TGRS