CleanUNet 2: A Hybrid Speech Denoising Model on Waveform and Spectrogram
Machine Learning
2023-09-13 v1 Sound
Audio and Speech Processing
Abstract
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.
Keywords
Cite
@article{arxiv.2309.05975,
title = {CleanUNet 2: A Hybrid Speech Denoising Model on Waveform and Spectrogram},
author = {Zhifeng Kong and Wei Ping and Ambrish Dantrey and Bryan Catanzaro},
journal= {arXiv preprint arXiv:2309.05975},
year = {2023}
}
Comments
INTERSPEECH 2023