5.2.7 Vocoders
The field of audio synthesis has undergone significant advancements in recent years, with various
approaches proposed to enhance the quality of synthesized audio. Prior studies have concentrated
on improving discriminator architectures or incorporating auxiliary training losses. For instance,
MelGAN introduced a multiscale discriminator that uses window-based discriminators at different
scales and applies average pooling to downsample the raw waveform. It enforces the correspondence
between the input Mel spectrogram and the synthesized waveform using an L1 feature matching
loss from the discriminator. In contrast, GAN-TTS [38] utilizes an ensemble of discriminators that
operate on random windows of different sizes and enforce the mapping between the conditioner
and the waveform adversarially using conditional discriminators. Another approach, parallel
WaveGAN [608], extends the single short-time Fourier transform loss to multi-resolution and
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