DeepJams: Machine Intelligence Meets Music Composition
DeepJams explores ways to augment traditional music composition with machine intelligence. We applied the latest research in the field along with the latest machine learning toolkits and artificial neural networks to train models that can extend original human compositions with equally original machine generated extensions.
Our group's focus centers on creating useable models which exceed not only on quantitative dataset benchmarking exercises for originality, but can also garner positive qualitative feedback for likeability via controlled user testing. To this end, we have created fully functional prototypes for every iteration of the academic effort, free for evaluation and use.