Deep Learning for Music

Understand

Our goal is to be able to build a generative model from a deep neural network architecture to try to create music that has both harmony and melody and is passable as music composed by humans.

• Previous work in music generation has mainly been focused on creating a single melody.
• More recent work on polyphonic music modeling, centered around time series probability density estimation, has met some partial success.
• In particular, there has been a lot of work based off of Recurrent Neural Networks combined with Restricted Boltzmann Machines (RNN-RBM) and other similar recurrent energy based models.