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

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