MusGU+ Framework

The Music-Generative Usable+ AI (MusGU+) framework is a musician-centered evaluation framework designed to assess how generative music models can be adapted, used, and controlled in real-world creative contexts. The framework evaluates models along three complementary dimensions, with each dimension addressing a key question from the musician's perspective:

Adaptability — Can I realistically adapt this model to my own data?
Usability — Can I access, run, and integrate this model into my music-making workflow?
Controllability — Can I guide the model in musically meaningful and interpretable ways?

📖 Read the detailed evaluation criteria

A Discovery Tool for Generative Music AI

Model ▴▾	Adaptability ▴▾ ≥60%					Usability ▴▾ ≥60%						Controllability ▴▾ ≥60%
	Hardware Requirements CPU+0	Dataset Size small dataset+0	Adaptation Pathways LoRAtrainingfine-tuningprior trainingpretrained codecpretrained checkpoints+0	Technical Barriers GUICLIColabconfigtutorialdrag-and-drop+0	Model Redistribution	Interface Availability AUVSTColabGradioweb UIMax/MSPiOS appPureDataMax4LiveAndroid appHugging Facestandalone app+0	Access Restrictions	Real-time Capabilities real-time+0	Workflow Integration DAWhardwarelive codingvisual programming+0	Output Licensing	Community Support ForumDiscordHelp centerGitHub IssuesGitHub Discussions+0	Conditioning Inputs tagstextMIDIaudiolyricstimingsectiontext prompt+0	Time-Varying Control	Feature Disentanglement pitchstylemelodytimbreloudnesssemanticsstructurebrightness+0	Control Parameters durationrandomnesslatent priorlatent noisediffusion stepssampling strategylatent manipulationlatent interpolationconditioning strength+0
DDSP-VST Google Magenta	~	✔︎	~	~	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎
Neutone Morpho Neutone Inc.	✔︎	✔︎	~	✔︎	~	✔︎	~	✔︎	✔︎	✔︎	✔︎	~	✔︎	~	✔︎
RAVE IRCAM	~	✔︎	✔︎	~	~	✔︎	✔︎	✔︎	✔︎	~	✔︎	~	✔︎	~	✔︎
AFTER IRCAM	~	~	✔︎	✘	~	✔︎	✔︎	✔︎	✔︎	~	~	✔︎	✔︎	✔︎	✔︎
SCAPES Music Technology Group, Universitat Pompeu Fabra	✔︎	✔︎	✔︎	~	✔︎	✔︎	✔︎	~	✘	✔︎	~	✔︎	✔︎	~	~
PLAUD Music Technology Group, Universitat Pompeu Fabra	~	✔︎	✔︎	~	~	✔︎	✔︎	✔︎	✔︎	~	~	~	✔︎	~	✔︎
Magenta RealTime 2 Google Magenta	✘	✘	✘	✘	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	✔︎	~	~
Stable Audio 3 Stability AI	~	✔︎	✔︎	✘	~	✔︎	✔︎	~	~	~	✔︎	~	~	✘	~
YuE The Hong Kong University of Science and Technology (HKUST) and MAP	✘	✘	✔︎	✘	✔︎	~	✔︎	✘	✘	✔︎	✔︎	~	~	~	~
JAM Singapore University of Technology and Design and Lamda Labs.	~	✘	✔︎	✘	~	~	✔︎	✘	✘	~	~	~	~	~	~
MusicGen Meta AI	✘	✘	✔︎	✘	~	~	✔︎	✘	✘	✔︎	~	~	~	~	~
Stable Audio Open Small Stablility AI	~	✘	✔︎	✘	~	~	~	~	✘	~	✔︎	~	~	✘	~
Suno Suno, Inc.	✘	✘	✘	✘	✘	✔︎	~	~	✘	~	✔︎	~	✘	✘	~
Udio Udio	✘	✘	✘	✘	✘	✔︎	~	~	✘	✘	✔︎	~	✘	✘	✘

How to navigate this table?

The MusGU+ framework evaluates models across 15 criteria distributed among three dimensions: Adaptability (5 criteria), Usability (6 criteria), and Controllability (4 criteria). Each criterion is evaluated on a three-level scale: ✔︎ fully supported, ~ partially supported, or ✘ not supported.

The table includes interactive elements:

Tag filters under Musical Applications or within criterion headers filter the table to show only models with those features.
Hover tooltips on evaluation cells reveal the comment or justification behind the assigned score.
Dimension headers reorder the table by that dimension, while the accompanying ≥60% button filters models that reach at least that threshold.
Model names open individual detail pages with resource links, musical applications, and criterion-level notes.

For the underlying evaluation files, explore the corresponding YAML entries in the projects folder.

Contributing

If you would like to help expand or refine MusGU+, there are two main ways to contribute:

Suggest a new model. The simplest option is to open an issue using the Suggest a New Model template. A brief explanation and any relevant links are enough; maintainers will take care of the detailed evaluation. More experienced contributors can instead create a new branch, add a YAML evaluation following the YAML template, and submit a pull request.
Propose changes to an existing evaluation. If you think a current model entry should be updated, corrected, or expanded, you can open an issue or submit a pull request with supporting evidence.

MusGU+: Musician-Centered Evaluation Framework

A Discovery Tool for Generative Music AI

Musical Applications

How to navigate this table?

Contributing

Relationship to MusGO