  Music has always been thought of as a "human" endeavor -- when praising a
piece of music, we emphasize the composer's creativity and the emotions the
music invokes. Because music also heavily relies on patterns and repetition in
the form of recurring melodic themes and chord progressions, artificial
intelligence has increasingly been able to replicate music in a human-like
fashion. This research investigated the capabilities of Jukebox, an open-source
commercially available neural network, to accurately replicate two genres of
music often found in rhythm games, artcore and orchestral. A Google Colab
notebook provided the computational resources necessary to sample and extend a
total of sixteen piano arrangements of both genres. A survey containing
selected samples was distributed to a local youth orchestra to gauge people's
perceptions of the musicality of AI and human-generated music. Even though
humans preferred human-generated music, Jukebox's slightly high rating showed
that it was somewhat capable at mimicking the styles of both genres. Despite
limitations of Jukebox only using raw audio and a relatively small sample size,
it shows promise for the future of AI as a collaborative tool in music
production.
