An Application for Evolutionary Music Composition Using Autoencoders

Robert Neil McArthur, Charles Patrick Martin

Abstract: This paper presents a new interactive application that can generate music according to a user’s preferences inspired by the process of biological evolution. The application composes sets of songs that the user can choose from as a basis for the algorithm to evolve new music. By selecting preferred songs over successive generations, the application allows the user to explore an evolutionary musical space. The system combines autoencoder neural networks and evolution with human feedback to produce music. The autoencoder component is used to capture the essence of musical structure from a known sample of songs in a lower-dimensional space. Evolution is then applied over this representation to create new pieces based upon previously generated songs the user enjoys. In this research, we introduce the application design and explore and analyse the autoencoder model. The songs produced by the application are also analysed to confirm that the underlying model has the ability to create a diverse range of music. The application can be used by composers working with dynamically generated music, such as for video games and interactive media.