Abstract:Most GAN(Generative Adversarial Network)-based approaches towards high-fidelity waveform generation heavily rely on discriminators to improve their performance. However, the overuse of this GAN method introduces much uncertainty into the generation process and often result in mismatches of pitch and intensity, which is fatal when it comes to sensitive using cases such as singing voice synthesis(SVS).To address this problem, we propose RefineGAN, a highfidelity neural vocoder with faster-than-real-time generati… Show more
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