Papers › CleanUNet 2: A Hybrid Speech Denoising Model on Waveform and Spectrogram
CleanUNet 2: A Hybrid Speech Denoising Model on Waveform and Spectrogram
Zhifeng Kong, Wei Ping, Ambrish Dantrey, Bryan Catanzaro
In this work, we present CleanUNet 2, a speech denoising model that combines the advantages of waveform denoiser and spectrogram denoiser and achieves the best of both worlds. CleanUNet 2 uses a two-stage framework inspired by popular speech synthesis methods that consist of a waveform model and a spectrogram model. Specifically, CleanUNet 2 builds upon CleanUNet, the state-of-the-art waveform denoiser, and further boosts its performance by taking predicted spectrograms from a spectrogram denoiser as the input. We demonstrate that CleanUNet 2 outperforms previous methods in terms of various objective and subjective evaluations.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Speech Enhancement | Deep Noise Suppression (DNS) Challenge | CleanUNet-2 | PESQ-NB | 3.658 | #12 of 36 | Archive leaderboard | report |
| Speech Enhancement | Deep Noise Suppression (DNS) Challenge | CleanUNet-2 | PESQ-WB | 3.262 | #12 of 36 | Archive leaderboard | report |
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