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Unified Signal Compression Using Generative Adversarial Networks

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IEEE ICASSP 2020 Virtual Conference May 2020

We propose a unified compression framework that uses generative adversarial networks (GAN) to compress image and speech signals. The compressed signal is represented by a latent vector fed into a generator network which is trained to produce high quality

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Unified Signal Compression Using Generative Adversarial Networks

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We propose a unified compression framework that uses generative adversarial networks (GAN) to compress image and speech signals. The compressed signal is represented by a latent vector fed into a generator network which is trained to produce high quality