Speech Denoising in the Waveform Domain with Self-Attention

• URL: http://arxiv.org/abs/2202.07790v1
• Date: Tue, 15 Feb 2022 23:44:02 GMT
• Title: Speech Denoising in the Waveform Domain with Self-Attention
• Authors: Zhifeng Kong, Wei Ping, Ambrish Dantrey, Bryan Catanzaro
• Abstract summary: 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.
• Score: 27.84933221217885
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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