Generating Real Time Adaptive Game Music

Abstract

This thesis aims to construct and train an LSTM-based machine learning model that can automatically generate real time adaptive video game music. In order to demonstrate its capabilities, a game using the model’s music is developed. A review of similar existing works and the methodology of the thesis is provided, as well as the analysis of the final product.