De-Mix Audio using FluCoMa in Max

Taught by: Ted Moore

Sunday 26th March 4pm UK, 5pm Berlin, 8am LA, 11am NYC

 

The first time I heard an example of what this algorithm can do, I was super impressed. It broke apart a mono drum loop into three tracks. One had only the snare sounds, one had only the kick drum sounds, and one had only the cymbal sounds. This sparked a lot of thinking about how I could use this for creativity. Then I found out it also can break apart and identify specific sounds in real-time audio. In this workshop I'll show you how these tools work in the FluCoMa toolkit and some of the ways I've been using it in my own work.

 

It's suggested that you have completed the FREE course: Using Machine Learning Creatively via FluCoMa in Max

Level

Starts on: 25/03/2023 16:00 London time

What you'll learn

  • De-mix recorded audio into sound objects
  • Deconstruct real-time audio streams
  • Identify important sounds in real-time audio
  • Seed this process to help the algorithm find the sound objects we're interested in

Course content

  • Open the course in Zoom to access all the features
Membership plan: Going Deeper | Topics: Sound Design ...

Access this course and 100s more for

From: £35 / month with a 7-day free trial

Subscribe
OR

Buy this course and own it forever

Requirements

  • A working PC, Laptop, iMac or MacBook
  • Max software
  • Download the FluCoMa Package from the Package Manager
  • A Zoom account
  • A mic and camera is recommended, but not necessary
  • It is suggested to first watch the free course Using Machine Learning Creatively via FluCoMa in Max

Who is this course for

  • Sound Designers searching for new ways of combining sounds
  • Audio Engineers intrigued by de-mixing possibilities
  • Creative artists interested in machine learning algorithms for music making

Useful links

About the workshop leader

Ted Moore (he / him) is a composer, improviser, and intermedia artist. He holds a PhD in Music Composition from the University of Chicago and recently served as a Research Fellow in Creative Coding at the University of Huddersfield, investigating the creative affordances of machine learning and data science algorithms as part of the FluCoMa project.‚Äč His work focuses on fusing the sonic, visual, physical, and acoustic aspects of performance and sound, often through the integration of technology.