Portfolio of compositions:
Creating electroacoustic compositions through the sonification of recursive neural networks
Exploring the creative use of in-training data for informational and monitoring purposes
The University of Manchester
This research will explore the sonification of data from recursive neural networks as a way to generate new, engaging musical materials, to create a portfolio of electroacoustic compositions that can provide some insights into how these networks operate, including the rate of data transformation and the effect of recurrent cells on that transformation. I hope this work can bring into focus the potential for human control in the use and design of deeplearning networks for creative purposes, and in algorithmic sonification.
Data sonification; music and sound-art; psychoacoustics; artificial intelligence