Improvement of Noise Suppression Performance of SEGAN by Sparse Latent Vectors
Minami Sakuma, Yosuke Sugiura, Tetsuya Shimamura · 2019
For the purpose of speech enhancement, SEGAN, which is one of deep generative models, has attracted attention due to its high performance. In this paper, we propose a method to sparse latent vectors to further enhance the noise suppression effect of SEGAN.