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TS-URGENet: A Three-stage Universal Robust and Generalizable Speech Enhancement Network

About

Universal speech enhancement aims to handle input speech with different distortions and input formats. To tackle this challenge, we present TS-URGENet, a Three-Stage Universal, Robust, and Generalizable speech Enhancement Network. To address various distortions, the proposed system employs a novel three-stage architecture consisting of a filling stage, a separation stage, and a restoration stage. The filling stage mitigates packet loss by preliminarily filling lost regions under noise interference, ensuring signal continuity. The separation stage suppresses noise, reverberation, and clipping distortion to improve speech clarity. Finally, the restoration stage compensates for bandwidth limitation, codec artifacts, and residual packet loss distortion, refining the overall speech quality. Our proposed TS-URGENet achieved outstanding performance in the Interspeech 2025 URGENT Challenge, ranking 2nd in Track 1.

Xiaobin Rong, Dahan Wang, Qinwen Hu, Yushi Wang, Yuxiang Hu, Jing Lu• 2025

Related benchmarks

TaskDatasetResultRank
Speech EnhancementURGENT Challenge 2025 (non-blind test)
DNSMOS3
19
Universal Speech EnhancementURGENT non-blind 2025 (test)
DNSMOS3
9
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