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    A machine learning approach called CycleGAN has been shown to be effective at transforming an image from one style to another. Perhaps turning a photo into a Monet-style painting, or changing a picture of a horse into that of a zebra. However, I wanted to try to use the approach on a more challenging transformation: turning audio data into an aesthetically-pleasing image to illustrate the latent structure of music.