Neat drummer : computer-generated drum tracks
Computer-generated music composition programs have yet to produce creative, natural sounding music. To date, most approaches constrain the search space heuristically while ignoring the inherent structure of music over time. To address this problem, this thesis introduces NEAT Drummer, which evolves a special kind of artificial neural network (ANN) called compositional pattern producing networks (CPPNs) with the NeuroEvolution of Augmenting Topologies (NEAT) method for evolving increasingly complex structures. CPPNs in NEAT Drummer input existing human compositions and output an accompanying drum track. The existing musical parts form a scaffold i.e. support structure, for the drum pattern outputs, thereby exploiting the functional relationship of drums to musical parts (e.g. to lead guitar, bru:is, etc.) The results are convincing drum patterns that follow the contours of the original song, validating a new approach to computergenerated music composition.
This item is only available in print in the UCF Libraries. If this is your thesis or dissertation, you can help us make it available online for use by researchers around the world by downloading and filling out the Internet Distribution Consent Agreement. You may also contact the project coordinator Kerri Bottorff for more information.
Stanley, Kenneth O.
Bachelor of Science (B.S.)
College of Engineering and Computer Science
Dissertations, Academic -- Electrical Engineering and Computer Science;Electrical Engineering and Computer Science -- Dissertations, Academic
Length of Campus-only Access
Honors in the Major Thesis
Hoover, Amy K., "Neat drummer : computer-generated drum tracks" (2008). HIM 1990-2015. 791.