Ks-Net: Multi-Band Joint Speech Restoration and Enhancement Network for 2024 ICASSP SSI Challenge

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Guochen Yu, Runqiang Han, Chenglin Xu, Haoran Zhao, Nan Li, Chen Zhang, Xiguang Zheng, Chao Zhou, Qi Huang, Bing Yu

Published: 01 Jan 2024, Last Modified: 14 Oct 2025ICASSP Workshops 2024EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: This paper presents the speech restoration and enhancement system created by the 1024K team for the ICASSP 2024 Speech Signal Improvement (SSI) Challenge. Our system consists of a generative adversarial network (GAN) in complex-domain for speech restoration and a fine-grained multi-band fusion module for speech enhancement. In the blind test set of SSI, the proposed system achieves an overall mean opinion score (MOS) of 3.49 based on ITU-T P.804 and a Word Accuracy Rate (WAcc) of 0.78 for the real-time track, as well as an overall P.804 MOS of 3.43 and a WAcc of 0.78 for the non-real-time track, ranking 1st in both tracks.