mlsanityData to 14 Oct 2026

Calliope: An Online Generative Music System for Symbolic Multi-Track Composition

arXiv 2504.14058 ↗First posted 18 Apr 2025cs.HC cs.LG cs.SDcited by 1

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Abstract (arXiv)

With the rise of artificial intelligence in recent years, there has been a rapid increase in its application towards creative domains, including music. There exist many systems built that apply machine learning approaches to the problem of computer-assisted music composition (CAC). Calliope is a web application that assists users in performing a variety of multi-track composition tasks in the symbolic domain. The user can upload (Musical Instrument Digital Interface) MIDI files, visualize and edit MIDI tracks, and generate partial (via bar in-filling) or complete multi-track content using the Multi-Track Music Machine (MMM). Generation of new MIDI excerpts can be done in batch and can be combined with active playback listening for an enhanced assisted-composition workflow. The user can export generated MIDI materials or directly stream MIDI playback from the system to their favorite Digital Audio Workstation (DAW). We present a demonstration of the system, its features, generative parameters and describe the co-creative workflows that it affords.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 11 references that are in the map. First posted on arXiv 18 Apr 2025.

Builds on

6 of 11 references.

References · 6

  1. 2018A Hierarchical Latent Vector Model for Learning Long-Term Structure in Musiccited by 131
  2. 2020MMM : Exploring Conditional Multi-Track Music Generation with the Transformercited by 49
  3. 2018MorpheuS: generating structured music with constrained patterns and tensioncited by 22
  4. 2020Quantifying Musical Style: Ranking Symbolic Music based on Similarity to a Stylecited by 6
  5. 2019A Minimal Template for Interactive Web-based Demonstrations of Musical Machine Learningcited by 4
  6. 2018DeepDrum: An Adaptive Conditional Neural Networkcited by 3

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