# Channel-Attention Dense U-Net for Multichannel Speech Enhancement

Source: [Channel-Attention Dense U-Net for Multichannel Speech Enhancement](<https://www.sota2.com/research/paper/68fa67021e209131cea13baf>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-12-25T07:42:55.399Z

Authors: Bahareh Tolooshams, Ritwik Giri, Andrew H. Song, Umut Isik, Arvindh Krishnaswamy

Published: 2020-01-30T19:56:52.000Z

## Abstract

Supervised deep learning has gained significant attention for speech enhancement recently. The state-of-the-art deep learning methods perform the task by learning a ratio/binary mask that is applied to the mixture in the time-frequency domain to produce the clean speech. Despite the great performance in the single-channel setting, these frameworks lag in performance in the multichannel setting as the majority of these methods a) fail to exploit the available spatial information fully, and b) still treat the deep architecture as a black box which may not be well-suited for multichannel audio processing. This paper addresses these drawbacks, a) by utilizing complex ratio masking instead of masking on the magnitude of the spectrogram, and more importantly, b) by introducing a channel-attention mechanism inside the deep architecture to mimic beamforming. We propose Channel-Attention Dense U-Net, in which we apply the channel-attention unit recursively on feature maps at every layer of the network, enabling the network to perform non-linear beamforming. We demonstrate the superior performance of the network against the state-of-the-art approaches on the CHiME-3 dataset.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Speech Enhancement on CHiME-3 sim (dev)](<https://www.sota2.com/research/sota/speech-enhancement-on-chime-3-sim-dev.md>): Speech Enhancement; CHiME-3 sim (dev); SDR: 17.169.

- [Speech Enhancement on CHiME-3 (sim-test)](<https://www.sota2.com/research/sota/speech-enhancement-on-chime-3-sim-test.md>): Speech Enhancement; CHiME-3 (sim-test); SDR: 18.635.

- [Speech Enhancement on CHiME-3](<https://www.sota2.com/research/sota/speech-enhancement-on-chime-3.md>): Speech Enhancement; CHiME-3; PESQ: 2.436.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2001.11542>)

[PDF](<https://arxiv.org/pdf/2001.11542.pdf>)