Compression-Controlled Feedback Loops in Your DAW

Creating DAW-based feedback loops, then using side-chain compression to regulate them.

Here, working on a project with @SpectralEvolver , I show in Logic Pro X how we can use a compressor side-chained to a beat to control a feedback loop for some noisy, industrial sounding music that sounds evocative of the artist Emptyset. I found this was a great way to create a chaotic sound, but keep it under control (and out of the way of the drums).

0:00 Intro
0:29 The audio tracks
1:15 Side-chain compression
2:03 The feedback loop
3:13 Controlling the loop with compression
5:00 Emptset
5:13 Two aux tracks sending to each other
6:23 A note about time-based effects
6:50 Will it blow up?!
8:06 Closing, next steps

Check out Emptyset’s bandcamp here. Here’s Emptyset talking about their ionospheric propagation work, “Signal”:

More Logic Pro Tutorials from me here:

Heart Beat to DrumBrute Impact Tempo with Apple Watch,, & Pure Data

Using, OSC, and Pure Data to send my heart rate from my Apple Watch to the Arturia DrumBrute Impact.

I got an Apple Watch a couple of weeks ago, and, of course, on the very first day I started looking into apps that would allow me to send the data coming from my watch out as OSC messages. After some poking around I found by Holonic Systems, and decided to give it a try.

There’s actually way more in this app than I actually needed (I just wanted to get all the physical data out to my laptop), but it suits the purpose. So in this video, I show a quick demo of getting my heart rate as an OSC message into my laptop running Pd, and then converting it into a MIDI clock for the drumbrute impact.

More on OSC in Pd Vanilla:

More Pure Data tutorials here.

Check prices on the Arturia DrumBrute Impact (affiliate links):
Perfect Circuit

Sending Raw MIDI Data in Max (and Pure Data)

Sending out raw MIDI data in Max/MSP with [midiout] for system messages and other live control.

Here, I use the [midiout] object in Max to send individual “note on” and “note off” messages, using our knowledge of the MIDI protocol. We can then expand that to algorithmic MIDI control of sequences in the Arturia DrumBrute Impact, including adjusting the clock and the song position pointer for funky, chaotic beats.

0:00 Intro
0:30 [midiout]
0:59 Basic concept – Note On
3:16 Note Off
4:32 Pitch Bend Change
5:32 Exploring Algorithmic Control
6:47 Controling Sequencers (DrumBrute Impact)
7:09 MIDI Clock Message
9:01 Algorithmic Clock Control
10:03 Start, Stop, and Continue MIDI Messages
11:29 Playing with the Song Position Pointer
13:30 Bringing back the Drunk [metro]
15:00 Closing / Next Steps

Click here for more Max/MSP videos:

Interactive Neural Net in Eurorack (Joystick & Artificial Neuron)

Combining human input from a joystick with a two-neuron artificial neural network for chaotic interactive music.

This Eurorack joystick is going into a simple neural network to control multiple dimensions of the timbre of this synth voice. Joystick dimensions X, Y, and Z go into different inputs of the Nonlinear Circuits Dual Neuron, and are mixed together and transformed by a nonlinearity (more here). In addition to the output controlling the waveform and filter cutoff of the synth, the outputs of each neuron is fed back into the other, creating a chaotic artificial organism with which to improvise.

Affiliate links for modules in this patch (though you really don’t need them; you can probably work this out with the gear or software that you currently have):
Doepfer A-174-4 3D Joystick (Perfect Circuit)
NLC Dual Neuron (Reverb)
Noise Engineering Ataraxic Translatron (Reverb)
Hikari Ping Filter (Perfect Circuit)
Noise Engineering Sinclastic Empulatrix (Reverb)
Arturia DrumBrute Impact (Perfect Circuit)
Korg SQ-1 (Perfect Circuit)

More Music with Artificial Neurons:

Spotting Subaudio

Finding and removing subaudio from sample files with a waveform editor.

Subaudio are frequencies below the range of human hearing (below 20Hz). These frequencies can sneak into our recordings, and work against us in a number of ways. If we can address subaudio in our samples, we can do ourselves a favor in the later stages of our mixing process.

0:00 Defining Subaudio
0:59 Example 1: Spotting Subaudio
2:04 Example 1: Doing the Math
2:50 Why Did This Happen?
3:11 Removing Subaudio with Parametric EQ
5:53 Example 2: Not Really Subaudio
7:27 Harmonics of Subaudio
8:31 Example 3: Trimming
9:15 Example 4: Bringing It All Together
10:16 Closing. Next Steps

The MIDI Protocol: System Messages

An overview of MIDI System messages and how they can support MIDI programming and synchronization in your studio.

I ran away from an explanation of system messages in my previous video on MIDI Messages, instead focusing entirely on channel messages. In this video, though, I’m back to talk about System Exclusive Messages, System Common Messages, and System Realtime Messages, and how you can implement them for additional musical control.

0:00 Introduction
0:22 Quick Review of bits and bytes
0:57 Channel vs. System Messages
1:59 Categories of System Messages
2:36 System Exclusive (SysEx) Messages
4:50 System Common Messages
5:08 Song Select, Song Position Pointer
6:38 MIDI Time Code
7:31 Time Code Quarter Frame Message
9:10 Tune Request Message
9:58 System Real Time Messages
10:41 Active Sensing
11:25 Reset Message
11:56 MIDI Clock, Start, Continue, & Stop
12:39 MIDI Sync Demo in Max
13:06 MIDI Sync Demo in Logic Pro X
13:26 Wrap-up

MIDI Protocol 1: Bits, Bytes, and Binary

MIDI Protocol 2: MIDI Messages

Nonlinear Data-Driven Instruments with Simple Artificial Neural Networks (Max/MSP)

Building a simple artificial neural network in Max/MSP for nonlinear, chaotic control of data-driven instruments.

I’ve talked before about data-driven instruments, and I’ve talked before about artificial neurons and artificial neural networks, so here I combine the ideas to use a simple neural network to give some chaotic character to incoming data from a mouse and joystick before converting into into MIDI music. The ANN (Artificial Neural Network) reinterprets the data in way that isn’t random, but also isn’t linear, perhaps giving some interesting “organic” sophistication to our data-driven instrument.

In this video, I work entirely with musical control in MIDI, but these ideas could also apply to OSC or directly to any musical characteristics (like cutoff frequency of a filter, granular density, etc.).

0:00 Intro
1:43 [mousestate] for Data Input
2:58 Mapping a linear data-driven instrument
7:19 Making our Artificial Neuron
15:27 Simple ANN
20:06 Adding Feedback
22:23 Closing Thoughts, Next Steps

More Max/MSP Videos:

More Artificial Neurons and Neural Networks: