Deep Learning for Music Composition

Research areas

Description

 

Machine Learning for Music Composition

I'm interested in modelling symbolic music using machine learning methods such as deep neural networks and the Long Short-Term Memory cell. The goal is to model the note choices (as represented by sheet music or midi files), rather than modelling audio waveforms. This topic has generated a lot of interest lately, with several notable examples including the exciting Magenta project from the Google Brain team.
 
Please take a look at my page for more information: 
 
 
I have several interesting projects to offer, and I'm open to suggestions for new ones. We would need to negotiate this based on your background and level of enthusiasm. Here are a few candidates:
 
- machine learning modelling
- interface design, to prototype tools which allow human composers to exploit our existing models
- evaluation framework, including the psychophysical design and software implementation of online web surveys for music evaluation
 
These should be really fun projects. I'm looking forward to hearing from you.

Requirements

The requirements depend on the eventual project definition. Most will require an aptitude for programming.

Keywords

machine learning deep learning neural networks music composition

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing