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Glow-WaveGAN: Learning Speech Representations from …
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GitHub - leiyi420/glow-wavegan2
WebApr 12, 2024 · Flow step. The normalizing flow step in Glow is composed of 3 operations: Affine Coupling Layer: A coupling layer which splits the input data along channel dimensions, using the first half to estimate parameters of a transformation then applied to the second half (similar to RealNVP).; ActNorm: Normalization layer similar to batch … WebJun 21, 2024 · Results demonstrate that the flow-based acoustic model can exactly model the distribution of our learned speech representation and the proposed TTS framework, namely Glow-WaveGAN, can produce high fidelity speech outperforming the state-of-the-art GAN-based model. PDF Abstract WebContribute to leiyi420/glow-wavegan2 development by creating an account on GitHub. grinch videos free