2^ndPHYLA COUNTERPOINT

Of Strings & Kings.

TABLE OF CONTENTS

⁰⁰

^Introduction

^1.0

^{Masks of Power}

^1.1

^{Mystification, Naturalization, & Literacy}

^1.2

^{Vectoralism: Content Isn’t King}

^1.3

^{AI & Intellectual Property: The Ownership of Possibility}

^2.0

^{Duets, Practice, & Play}

^2.1

^{Xeno-Duets & Learning Systems}

^2.2

^{You Can’t Teach An Old Form New Tricks: Overfitting, Underfitting, Bias, & Variance}

^2.3

^{Practice Makes Perfect

Practice Makes Permanent}

^2.4

^{Pattern Recognition, Improvised Learning, & Entanglement}

^3.0

^{Tuning Systems & Hyperparameters}

^3.1

^{Machinic Metaphysics: Trancendental Number and Harmony as Cosmology}

^3.2

^{Retuning, Retraining, & Recalibrating}

^3.3

^{Hyperparameters, Cultural Luthiery, and Sacred Tuning Systems}

^4.0

^Afterward

^4.1

^{Metanoia & Remodeling Indeterminacy}

^A

^{Appendix A: Ancillary Musical Contextualization}

^B

^{Appendix B: Algorithms & Library Implementations}

^{Cullen Miller}

I’m a systems artist, spatial media designer, and composer. ︎︎︎

^{︎ ︎

︎}

^Home︎

B

Appendix B:
Algorithms & Library Implementations

SampleRNN

An Unconditional End-to-End Neural Audio Generation Model https://arxiv.org/abs/1612.07837
https://github.com/soroushmehr/sampleRNN_ICLR2017
https://github.com/richardassar/SampleRNN_torch

MIDI RNN

LSTM Recurrent Neural Network made with Keras
https://github.com/brannondorsey/midi-rnn

Magenta & GANSynth

Char RNN

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow
https://github.com/sherjilozair/char-rnn-tensorflow/

WaveGAN

WaveGAN: Raw audio synthesis with generative adversarial networks
https://github.com/chrisdonahue/wavegan

GRUV

GRUV is a Python project for algorithmic music generation
https://github.com/MattVitelli/GRUV

Audio Style Transfer

TensorFlow implementation for audio neural style
https://github.com/vadim-v-lebedev/audio_style_tranfer