SF-Net

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The implementation of "Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Band Speech Enhancement"

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### SF-Net for fullband SE
This is the repo of the manuscript "Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Full-Band Speech Enhancement". Some audio samples are provided here and the code for GCRN-full, DS-Net-full, CTS-Net-full and the network configuration of SF-Net are released.

Abstract：Due to the high computational complexity to model more frequency bands, it is still intractable to conduct real-time full-band speech enhancement based on deep neural networks. Recent studies typically utilize the compressed perceptually motivated features with relatively low frequency resolution to filter the full-band spectrum by one-stage networks, leading to limited speech quality improvements. In this paper, we propose a coordinated sub-band fusion network for full-band speech enhancement, which aims to recover the low- (0-8 kHz), middle- (8-16 kHz), and high-band (16-24 kHz) in a step-wise manner. Specifically, a dual-stream network is first pretrained to recover the low-band complex spectrum, and another two sub-networks are designed as the middle- and high-band noise suppressors in the magnitude-only domain. To fully capitalize on the information intercommunication, we employ a sub-band interaction module to provide external knowledge guidance across different frequency bands. Extensive experiments show that the proposed method yields consistent performance advantages over state-of-the-art full-band baselines.

### [Demo page of audio samples](https://yuguochencuc.github.io/sfnet_demo/) 
(https://yuguochencuc.github.io/sfnet_demo/)

### System flowchart of SF-Net
![image](https://user-images.githubusercontent.com/51236251/160518968-0a074c93-7400-467c-9c16-2887f8466737.png)

### Results:
## Abaltion study
![lQLPDhtH56hfHqXNAjHNA7OwrtrfF1S_QEECRntyY8DWAA_947_561](https://user-images.githubusercontent.com/51236251/160519109-49617410-5611-4abb-85fc-d30e13225280.png)

## Comparison with SOTA
![lQLPDhtH6ITooSDNAz7NA7GwySl8YbYqe-8CRnzbbEA6AA_945_830](https://user-images.githubusercontent.com/51236251/160519878-e0aa93ea-9573-40f9-9665-2d8de9d90efe.png)

## Visualization of spectrograms
## VB dataset
![lQLPDhtH6NmMG6rNAwTNA6uw8qUBkZFtUxgCRn1lwQBsAA_939_772](https://user-images.githubusercontent.com/51236251/160520076-b580c1bb-253c-44ee-a781-1243caa7924d.png)
## DNS blind set
![lQLPDhtH8iT2-N_NAubNA42wBREh0WKHv5wCRoygD0BOAA_909_742](https://user-images.githubusercontent.com/51236251/160527589-97dff384-cb72-4354-8ab0-1f953ab5564c.png)

SF-Net

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