FARM 2026 – Preliminary Table of Contents

14th ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design (FARM 2026)

Frontmatter

14th ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design (FARM 2026) Papers

AGR: A Rehearsal-to-Performance Workflow for Programming Audio Gestures in Max
Hongshuo Fan
(Texas A&M University, USA; Royal Northern College of Music, UK)
Musical Audio Gesture Recognition (AGR) is a Max-based workflow for turning rehearsal-time audio gestures into programmable performance actions. Rather than treating recognition as a fixed classifier inserted into a finished composition, AGR keeps gesture vocabulary design, dataset capture, feature representation, model training, and output routing editable inside the same patching environment used in rehearsal and performance. Built on top of FluCoMa, AGR provides an integrated capture--training--runtime pipeline that combines fixed-length padding without time warping, a local frequency-deviation representation derived from sinusoidal peaks, and deployment patches that expose recognized gestures as OSC, MIDI, or gesture-bound audio triggers.
We frame AGR as a programmable artistic workflow: performers and composers define what counts as a gesture, test recognition behavior against rehearsal examples, and revise mappings or thresholds as part of the compositional process. We characterize the workflow across four instrument-specific datasets (clarinet, flute, trumpet, trombone), using recognition behavior and post-trigger processing time as practical checks on rehearsal use rather than as benchmark endpoints. We also discuss deployments ranging from single-instrument prototypes to concert works and a 12-model large-ensemble production. In these settings, AGR is part of the performance patch: gesture labels, training examples, thresholds, and routing decisions can be revised in rehearsal while the concert setup remains continuous.

Article Search Article: icfpws26farmmain-p4-p doi:10.1145/3830435.3830948

Composition: Building Community with Arts, Math, and Code (Experience Report)
Isidore Mohr and Claire Wang
(Independent Researcher, USA; University of Pennsylvania, USA)
Composition is a free event series on art, mathematics, and code. This experience report covers Composition's event structure, artist selection process, outreach efforts for submissions and event promotion, and the community response.

Article Search Article: icfpws26farmmain-p6-p doi:10.1145/3830435.3830949

Demo: The Reduction of Girard’s Paradox as Music
Isidore Mohr
(Independent Researcher, USA)
A translation of the reduction behavior of Girard's paradox into music using Soundproof, a tool for making music from terms of the dependently typed lambda calculus. I present the extension of the tool from single-term to reduction-based translation, and discuss points of choice in the small-step interpreter and its musical output.

Article Search Article: icfpws26farmmain-p8-p doi:10.1145/3830435.3830950

The Art of Concert Programming
Jared Gentner
(Independent Researcher, USA)
The process of preparing a program for a live performance is an extremely fulfilling one, not only because it can be artistically and spiritually rewarding, but also because it can be a technical challenge much like designing computer programs or systems. Performances may embed various art forms, such as song, dance, lighting and stage-play. The mediums for coordinating such performances are varied and rarely precise. We construct and describe Programmart, a specification language for writing concert programs, which leverages programming language features to handle the intricacies of crafting a live performance.

Article Search Article: icfpws26farmmain-p48-p doi:10.1145/3830435.3830951

CounterChoice: Counterpoint Composition in Dusa with a Firmus Foundation
Ahmet Yigit Erdem, Ari Prakash, Carlo Angiuli, Rose Bohrer, James McCann, Chris Martens, and Youyou Cong
(Institute of Science Tokyo, Japan; Middle East Technical University, Türkiye; Northeastern University, USA; Indiana University, USA; AIST, Japan; Carnegie Mellon University, USA)
This paper presents CounterChoice, a mixed-initiative creative application which creates a first-species counterpoint composition together with its user. The user provides the first voice, the cantus firmus, through a graphical interface provided as a web application, and CounterChoice generates the counterpoint voice using a logic program written in the finite-choice logic programming language Dusa. The resulting composition is presented both as playable audio and as Dusa code, at which point the user may continue to edit and revise via the same interaction loop. The CounterChoice experiment serves as both a demonstrator application for the Dusa language and a case-study in the development of domain-specific interfaces for modern logic programming languages, so that creators in those domains may access the full potential of such languages for procedural content generation and exploratory play. We present findings on the suitability of Dusa for encoding the formal rules of counterpoint, the impact of Dusa on the frontend interface, and generalizable design recommendations for developers of logic programming languages with similar applications to Dusa.

Article Search Article: icfpws26farmmain-p70-p doi:10.1145/3830435.3830952

Demo: Drawing Algorithms as Modular Objects: A Framework for Procedurally Generated Visual Arts and Music
Xingyu Dong, Daniel Průša, Michael Wehar, and Chen Xu
(University of Pennsylvania, USA; Czech Technical University, Czech Republic; Haverford College, USA; University at Buffalo, USA)
We developed a framework in JavaScript for procedurally generating visual artworks and music. This framework specifies how drawing algorithms are structured to step-by-step create images. While images are being generated, drawing actions are (optionally) converted to sounds to create music. Drawing algorithms are treated as objects that carry a state that changes over time. The current state determines how the next drawing step adds to and manipulates the image canvas. Drawing algorithms can run independent of each other with a collection of premade functionalities such as initialize, start, pause, reset, and drawOneStep. Furthermore, drawing algorithms can be passed as input into functions allowing them to run under a variety of configurations and be connected to user interfaces and external applications.
Furthermore, using this framework, we present a particularly interesting example of a drawing algorithm that has a dual purpose for both visually representing solutions to an algorithmic problem and for creating unique artworks. This algorithmic problem is defined as follows. Given an m by n binary matrix, our task is to enumerate all rectangular blocks containing only 1 entries on the border and 0 entries within the interior. The authors previously developed a solution for this problem that runs in O(m · n) time using O(n) space. We adapt this solution to create a drawing algorithm that draws visual artworks in the style of visionary artist Piet Mondrian and contemporary artist Adam Lister.

Article Search Article: icfpws26farmmain-p73-p doi:10.1145/3830435.3830953

Prismriver: Formalization of Music Theory and Algorithmic Composition in Lean 4
Leni Aniva and Claire Wang
(Stanford University, USA; University of Pennsylvania, USA)
Music theory obeys a rich set of mathematical rules and symmetries. These symmetries follow mathematical structures which can be verified and expressed in the precise language of a proof assistant. In this paper, we present Prismriver, a formalization library of music theory in Lean 4. We use Prismriver to generalize beyond existing work that assumes equal temperament tuning. We also discuss modelling counterpoint music theory with Prismriver. By formalizing music theory in Lean 4, we open the door to verifiable algorithmic composition and accompaniment generation. Prismriver also has a custom DSL integrated with MusicXML exports to interoperate with other music software. Prismriver can be used to compose music with Lean, using monadic composition primitives.

Article Search Article: icfpws26farmmain-p93-p doi:10.1145/3830435.3830954

14th ACM SIGPLAN International Workshop on Functional Art, Music, Modelling, and Design (FARM 2026)

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