Reviews: MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis

Quality: This paper suffers from a few critical issues. Clarity: The experiment setting ups can be described with more details. Sec 3.2 and 3.4 is missing important information such as the datasets used for conducting the experiments. Significance: Although the quality of the proposed model remains unclear because of the previously mentioned critical issues, it's a significant work because it's the first GAN-based model for spectrogram-to-waveform conversion which seems to be working at some degree. It's significantly over-claimed: 1) claiming state-of-the-art for spectrogram-to-waveform conversion (line 6) with MOS 3.09 is surprising; many previous works are at a much higher level (e.g.