2020年度 人工知能学会全国大会(第34回)

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国際セッション » E-2 Machine learning

[2K4-ES-2] Machine learning: GAN

2020年6月10日(水) 13:50 〜 15:30 K会場 (jsai2020online-11)

座長:Ahmed Moustafa(名古屋工業大学)

13:50 〜 14:10

[2K4-ES-2-01] Transfer symbolic music style from latent representation

〇Yingfeng Fu1, Yusuke Tanimura2,1, Hidemoto Nakada2,1 (1. The University of Tsukuba, 2. AIST)

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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