Visual Music Performance with Machine Learning - On demand hero

Creative Coding

Visual Music Performance with Machine Learning - On demand

Build an audiovisual performance system in openFrameworks, combining a Phong-lit 3D sphere with vertex displacement, an ofxMaxim FM synth, and a trained machine-learning model controlled over OSC.

Level

Advanced

Duration

1h 45m of video content

Format

Self-paced video

Added

03/11/2021

Course overview

An openFrameworks build that pairs real-time graphics with audio-reactive control. The session works up a displaced sphere with Phong lighting, a camera and normal matrix, and vertex displacement, then adds sound through ofxMaxim and a simple FM synth. From there it brings in machine learning, collecting gesture data, training and running a model, and mapping it via an OSC controller so visuals and sound respond together in performance.

Learning outcomes

Create generative visual art in openFrameworks

Create procedural audio in openFrameworks using ofxMaxim

Discuss interactive machine learning techniques

Use a neural network to control audiovisual parameters simultaneously in real-time

Who is this course for?

  • In this workshop you will use openFrameworks to build a real-time audiovisual instrument. You will generate dynamic abstract visuals within openFrameworks and procedural audio using the ofxMaxim addon. You will then learn how to control the audiovisual material by mapping controller input to audio and visual parameters using the ofxRapid Lib add on.

Requirements

  • A computer and internet connection
  • A web cam and mic
  • A Zoom account
  • Installed version of openFrameworks
  • Downloaded addons ofxMaxim, ofxRapidLib
  • Access to MIDI/OSC controller (optional - mouse/trackpad will also suffice)

Course content

What you will learn in this course

1 resource, 3 lessons

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  • Course Overview
  • Requirements
  • Pre-course preparation
  • Work sheet with exercises

Visual Music Performance with Machine Learning - On demand

9 videos, 2 lessons

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  • Part 1 - Sphere setup
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  • Part 2 - Phong lighting
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  • Part 3 - Camera + Normal matrix
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  • Part 4 - Vertex displacement
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  • Part 5 - ofxMaxim setup
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  • Part 6 - Simple FM synth
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  • Part 7 - Machine Learning - Data collection
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  • Part 8 - Machine Learning - Train + Run model
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  • Part 9 - OSC controller
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  • Finished Project on Github
  • Was this course the right level?

Instructors

Bryan Dunphy

Bryan Dunphy

Instructor

Bryan Dunphy graduated in 2021 from a PhD at Goldsmiths University. He specialises in audio-visual, immersive performances and creations. Most of his work uses Machine Learning.