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arXiv · 2202.07790

Speech Denoising in the Waveform Domain with Self-Attention

Zhifeng Kong·Wei Ping·Ambrish Dantrey·Bryan Catanzaro
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Abstract

In this work, we present CleanUNet, a causal speech denoising model on the raw waveform. The proposed model is based on an encoder-decoder architecture combined with several self-attention blocks to refine its bottleneck representations, which is crucial to obtain good results. The model is optimized through a set of losses defined over both waveform and multi-resolution spectrograms. The proposed method outperforms the state-of-the-art models in terms of denoised speech quality from various objective and subjective evaluation metrics. We release our code and models at https://github.com/nvidia/cleanunet.

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BibTeXRIS

Zhifeng Kong, Wei Ping, Ambrish Dantrey, Bryan Catanzaro. 2022-02-15. Speech Denoising in the Waveform Domain with Self-Attention. https://arxiv.org/abs/2202.07790

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