[R] WaveGAN: Synthesizing Audio with Generative Adversarial Networks • r/MachineLearning

I don't see why you're so eager to bash this that hard. Most GAN papers work on images 128x128 which is about the sample size in 1s audio, and even with the most clever tricks so far like LAPGAN or PGGAN the best is about 1024x1024 images. This is the very first published GAN model that is successfully trained with 1-D convolutions without skip connections - which means that it can generate audio samples with completely unsupervised fashion directly from latent samples. Can you imagine the new possibilities on generative audio modeling stemming from this, like people did on images during last couple years? Also, people created videos from frames obtained from CycleGAN and they didn't linearly scale everything like you like to do so much.