[P] MelGAN vocoder implementation in PyTorch
Disclaimer: This is a third-party implementation. The original authors stated that they will be releasing code soon.
A recent research showed that fully-convolutional GAN called MelGAN can invert mel-spectrogram into raw audio in non-autoregressive manner. They showed that their MelGAN is lighter & faster than WaveGlow, and even can generalize to unseen speakers when trained on 3 male + 3 female speakers’ speech.
I thought this is a major breakthrough in TTS reserach, since both researchers and engineers can benefit from this fast & lightweight neural vocoder. So I’ve tried to implement this is PyTorch: see GitHub link w/ audio samples below.
Debugging was quite painful while implementing this. Changing the update order of G/D mattered much, and my generator’s loss curve is still going up. (Though results looks good when compared to original paper’s.)