FluCoMa Workshop Summer 2024
Time: 12pm-3:30pm (with breaks) & 4:30pm-5:30pm USA East Coast Time
(asynchronous participation is allowed)
Location: Classes Held on Zoom
Instructor: Ted Moore
Cost: $100 USD (no one turned away for lack of funds)
To Register: email me stating:
- your interest
- your experience with Max and/or SuperCollider
- any prior experience with machine learning or artificial intelligence (none required!)
I’ll be capping enrollment at 20 participants.
Workshop Description
See schedule of topics below
This workshop will introduce and go in-depth on the Fluid Corpus Manipulation project (FluCoMa), a toolkit for making music with machine listening and machine learning within Max, SuperCollider, & Pure Data.
FluCoMa (https://www.flucoma.org/) is a toolkit for making music with machine listening and machine learning within Max, SuperCollider, & Pure Data. The toolkit offers audio decomposition tools to separate real-time and recorded audio into component elements, audio analysis tools to describe audio components as analytical and statistical representations, data analysis and machine learning algorithms for pattern detection and expressive corpus browsing, and audio morphing and hybridization algorithms for audio remixing, interpolating, and variation-making.
Participants will learn to use most aspects of the FluCoMa toolkit–with an emphasis on creative musical applications and outcomes. The math and theory behind these tools and algorithms will discussed when appropriate for building fluency and intuition towards artistic uses of FluCoMa. 12-3:30pm will be spent on lectures and code dissection while 4:30-5:30pm will be an opportunity for ideation, discussion, and instructor support on individuals’ projects.
Participants may use either Max or SuperCollider. Pure Data users are welcome knowing that Pure Data won’t be represented in the course materials.
Who is this workshop for?
Musicians and researchers interested in incorporating machine listening and machine learning tools in their creative practice. No prior knowledge of these topics is necessary.
Prerequisites:
Comfort using Max or SuperCollider for creative music projects. This course will not include introducing users to the basics of Max or SuperCollider.
Schedule
Subject to change based on the flow of the week!
Day 1: Neural Networks & Supervised Learning
- Working with data in FluCoMa
- Timbral Classification with MFCCs
- Regression for manipulating high-dimensional control spaces
- Neural Network prediction using real-time audio descriptors
Day 2: Temporal & Spectral Decomposition
- Slicing Audio in Time
- Sinusoidal Modelling
- Harmonic-Percussive Source Separation
- Spectral Decomposition with NMF (Non-negative Matrix Factorization)
Day 3: Audio Analysis & Plotting
- Audio descriptor analysis
- Statistical Analysis
- Plotting Data in FluCoMa
Day 4: Dimensionality Reduction & Unsupervised Learning
- KDTree
- Concatenative Synthesis
- Distance as a Measure of Similarity
- Scalers: Normalization, Standardization, & Robust Scaler
- Dimensionality Reduction with
- Principal Component Analysis (PCA)
- Uniform Manifold Approximation and Projection (UMAP)
Day 5: Misc., Presentations, & Next Steps
- Wavetable Autoencoder
- Seeding NMF
- Automatic Buffer & Dataset Management
- Presentations by participants sharing projects or progress from the week