Cluster 9 - University of California, San Diego
Transcript of Cluster 9 - University of California, San Diego
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Cluster 9 ☁Satvik N, Elena A, Conan L
Cluster 9 ☁Satvik N, Elena A, Conan L
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The Objective
Generate music using machine learning.
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HypothesisWe can utilize the GAN model to generate music, by training the algorithm on chroma and piano roll pairs.
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GenerativeAdversarialNetwork
What is a GAN?
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EXAMPLE
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The Concept● As the generator gets better at coloring the
image, the discriminator gets better at detecting which one is the fake/original.○ Positive feedback loop
● The end product is a generator that can make images that appear real
● We theorize that we can use the same model to generate music.
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PHASE 1TRAINING THE GAN - Successfully generate
music using chromas
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Chromas encapsulate the chords and general prevalence of notes in a song. Chroma puts every note on a 12 value spectrum to provide a visual representation of the notes in a musical piece.
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Training Data122 songs, all transposed to the key of C/Am, with their respective chromas
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PHASE 2USE THE GENERATOR - Convert music in other
genres to pop
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ExtensionConvert music in one style (i.e. classical) into another genre.
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Because the GAN has only been exposed to pop music, the chroma that the user inputs will be made into a piano score in the style of pop.
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Conclusion● Hypothesis somewhat supported by success
in converting Canon in D● A variety of music genres with several pieces
must be tested to truly test our hypothesis● Future development: train the computer
extensively and manually adjust the GAN algorithm to match our needs
● Learned a lot about machine learning, music theory, and working with Python
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AcknowledgementsWe’d like to thank all of the people who have taught us in these last four weeks and helped us with our final project:
● Shlomo Dubnov, professor of Computer Music at UCSD● Jacob Sundstrom, Ph.D student of computer music● Mauricio de Oliveira, professor of Mechanical & Aerospace Engineering at UCSD● Aren Akian, Ph.D student of computer science● Gualter Moura, teacher fellow● Everyone from Cluster 9 ☁
● and viewers like you :)
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Questions?