13:50 〜 14:10
[2K4-ES-2-01] Transfer symbolic music style from latent representation
キーワード:GAN, CycleGAN, Style transfer
Generative models has been widely applied in many computer vision scenarios. Two series of models, GenerativeAdversarial Network(GAN) and Variational Autoencoder(VAE), are getting more and more popular in represen-tation learning. Training these model on discrete sequence data generation is still challenging. We want to takeadvantage of both kind of models. In this work, we first improved a CycleGAN based model to transfer MIDI musicgenre. Then we want to find to combine the CycleGAN model together with a disentangled latent representationfrom VAE to have better understanding of music style.
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