Conditional WaveGAN
September 27, 2018 ยท Entered Twilight ยท ๐ arXiv.org
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Repo contents: .gitignore, LICENSE, README.md, data, dependencies, examples, final_presentation, gpu, paper_draft, tpu
Authors
Chae Young Lee, Anoop Toffy, Gue Jun Jung, Woo-Jin Han
arXiv ID
1809.10636
Category
cs.CV: Computer Vision
Cross-listed
cs.LG
Citations
22
Venue
arXiv.org
Repository
https://github.com/acheketa/cwavegan
โญ 128
Last Checked
1 month ago
Abstract
Generative models are successfully used for image synthesis in the recent years. But when it comes to other modalities like audio, text etc little progress has been made. Recent works focus on generating audio from a generative model in an unsupervised setting. We explore the possibility of using generative models conditioned on class labels. Concatenation based conditioning and conditional scaling were explored in this work with various hyper-parameter tuning methods. In this paper we introduce Conditional WaveGANs (cWaveGAN). Find our implementation at https://github.com/acheketa/cwavegan
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