most citedSVSGAN: Singing Voice Separation via Generative Adversarial Network

5 citations · 5 across the 1 of their papers we have counts for

collaborators

1 paper

cs.SD2017★ 5 cited

SVSGAN: Singing Voice Separation via Generative Adversarial Network

Zhe-Cheng Fan, Yen-Lin Lai, Jyh-Shing Roger Jang

Separating two sources from an audio mixture is an important task with many applications. It is a challenging problem since only one signal channel is available for analysis. In th…