  Entertainment-oriented singing voice synthesis (SVS) requires a vocoder to
generate high-fidelity (e.g. 48kHz) audio. However, most text-to-speech (TTS)
vocoders cannot reconstruct the waveform well in this scenario. In this paper,
we propose HiFi-WaveGAN to synthesize the 48kHz high-quality singing voices in
real-time. Specifically, it consists of an Extended WaveNet served as a
generator, a multi-period discriminator proposed in HiFiGAN, and a
multi-resolution spectrogram discriminator borrowed from UnivNet. To better
reconstruct the high-frequency part from the full-band mel-spectrogram, we
incorporate a pulse extractor to generate the constraint for the synthesized
waveform. Additionally, an auxiliary spectrogram-phase loss is utilized to
approximate the real distribution further. The experimental results show that
our proposed HiFi-WaveGAN obtains 4.23 in the mean opinion score (MOS) metric
for the 48kHz SVS task, significantly outperforming other neural vocoders.
