Software Projects

Network Modulation Synthesis

As part of my thesis work, I created compositional algorithms for autoencoder neural networks. The algorithms were implemented in a software package using the CANNe autoencoder (Joseph Colonel et al., DAFx 2018 ) as the base model.

The network modulation synthesis framework involves building up generative synthesis trees using the autoencoder network and generating multiple channels of related audio by altering each node’s encoding, feedback amount and feedback type. On top of traditional DSP-style feedback, a predictive feedback algorithm can be used, inspired by the Dreaming algorithm for LSTMs (Pfalz et al., ICMC 2018).

This work is being presented at ICMC 2021, check out the paper in the 2020 Selection (or here’s a direct link). You can find the code on Github, and additional audio examples here. And see my Compositions page for three compositions created using these methods!

Audio Effects for the OWL Guitar Pedal

As part of a Digital Signal Processing course, I created several implementations of guitar effects for the open source OWL Pedal.

The effects can be found on my author page for Rebel Technology. All effects were created using C++ or gen (a component of Max). Have fun with this effect in particular, which you may find amusing and not particularly useful.