most citedUniversal Score-based Speech Enhancement with High Content Preservation

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

eess.AS2024★ 2 cited

Universal Score-based Speech Enhancement with High Content Preservation

Robin Scheibler, Yusuke Fujita, Yuma Shirahata +1

We propose UNIVERSE++, a universal speech enhancement method based on score-based diffusion and adversarial training. Specifically, we improve the existing UNIVERSE model that deco…