Generating Music using Deep Learning

Deep learning has radically transformed the fields of computer vision and natural language processing, in not just classification but also generative tasks, enabling the creation of unbelievably realistic pictures as well as artificially generated news articles. In this project, we aim to create novel neural network architectures to generate new music, using 20,000 MIDI samples of different genres from the Lakh Piano Dataset, a popular benchmark dataset for recent music generation tasks. This project was a group effort by Isaac Tham and Matthew Kim, senior-year undergraduates at the University of Pennsylvania. Music generation using deep learning techniques has been a topic of interest for the past two decades. Music proves to be a different challenge compared to images, among three main dimensions: Firstly, music is temporal, with a hierarchical structure with dependencies across time. Secondly, music consists of multiple instruments that are interdependent and unfold across time.