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Improve GAN-based Neural Vocoder using Pointwise Relativistic LeastSquare GAN
[article]
2021
arXiv
pre-print
GAN-based neural vocoders, such as Parallel WaveGAN and MelGAN have attracted great interest due to their lightweight and parallel structures, enabling them to generate high fidelity waveform in a real-time manner. In this paper, inspired by Relativistic GAN, we introduce a novel variant of the LSGAN framework under the context of waveform synthesis, named Pointwise Relativistic LSGAN (PRLSGAN). In this approach, we take the truism score distribution into consideration and combine the original
arXiv:2103.14245v2
fatcat:zzzjs7xdsffjna5qrv5xytvl7y