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Generating Pop Songs through Machine Learning and Algorithms
dc.contributor.authorDavid Wang
dc.contributor.advisorÖzcan, Zeynep
dc.date.accessioned2021-09-21T20:31:13Z
dc.date.available2021-09-21T20:31:13Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/2027.42/169553
dc.description.abstractThis project explores the potential of recreating pop song melodies with computer science. Two approaches were taken. The first approach was through training Google Magenta's models. The second approach was writing hard-coded algorithms for music generation in Python.
dc.subjectcomputer science
dc.subjectmusic
dc.titleGenerating Pop Songs through Machine Learning and Algorithms
dc.typeProject
dc.contributor.affiliationumElectrical Engineering and Computer Science
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/169553/1/tawei_capstone_report.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/169553/2/tawei_capstone_slides.pptx
dc.identifier.doihttps://dx.doi.org/10.7302/2598
dc.working.doi10.7302/2598en
dc.owningcollnameHonors Program, The College of Engineering


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