Some recent or current Algomus projects

MICCDroP

MICCDroP

MICCDroP: Mixed Initiative Co-Creative Design for Long-Term Human-AI Musical Partnerships explores AI methods for lifelong learning and agent personalization within music generation, using reinforcement and curiosity-driven learning. The impact of these long-term adaptations will then be critically evaluated during artistic collaborations, through the lenses of ethnographic studies and computational creativity theory.

Project members: Ken Déguernel (PI, CR), Florent Berthaut (MCF HDR), Claudio Panariello (Post-doc), Ziyun Liu (PhD student)
➡️ Website (soon)

ANIMA

ZgotmplZ
In collaboration with the MTG at University Pompeu Fabra (Barcelona), ANIMA aims to develop a theoretical and practical computational framework for microtonal music co-creation, focusing on 53-TET tuning. It combines computational modeling with music theory and computational musicology, to design new harmonic models, and build interactive visualisation tools for real-time experimentation.

Project members: David Dalmazzo (PI, Post-doc, MTG), Ken Déguernel (CR), Mathieu Giraud (DR), Sergi Jordà (Associate Professor, MTG)
➡️ Publication NIME 2025

Co-creative Music Generation with Ur

Holly Herndon

Ur is a modular generative framework for co-creative music and other artistic artifacts. It is based on concepts from procedural generation, combined with ideas from machine learning and computational creativity.
➡️ Code // Holly Herndon’s Exhibitions The Call (London, 2024) and Starmirror (Berlin, 2025)

TABASCO, Tablature Assisted Composition

Guitar chords

The TABASCO project aims to develop algorithmic tools to assist guitar composition in contemporary music styles (pop, rock, metal, jazz, etc.). It studies how guitarists compose and how tablature software shapes their creative process.
➡️ Details // Publications // Alexandre D’Hooge PhD

Dezrann, Interacting, Sharing, Analyzing Music Corpora

Analysis of the Bach fugue in C minor BWV847 with Dezrann

Dezrann is an open web platform designed to listen to, study, and annotate music. Users directly interact with views on music sources, such as scores, waveforms, grids, or piano rolls. Dezrann’s applications span music education, as well as corpus annotation and interaction for research in musicology and computer music.
➡️ Details // Dezrann web app // Code // Publication TISMIR 2025