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D²Net: A Denoising and Dereverberation Network Based on Two-branch Encoder and Dual-path Transformer

21 Nov 2022APSIPA ASC 2022 11archive 2025-07-28

Liusong Wang, Wenbing Wei, Yadong Chen, and Ying Hu

The simultaneous denoising and dereverberation for single-channel mixture speech under the complicated acoustic environment is considered to be a challengeable task. In this paper, we propose a denoising and dereverberation network named as D²Net in which a two-branch encoder (TBE) is designed to extract and selectively fuse features with different granularity. In addition, we design a global-local dual-path transformer (GLDPT) which introduces the local dense synthesizer attention (LDSA) in the dual-path transformer to improve the perception of local information. We evaluated our proposed D²Net and conducted ablation studies on the VoiceBank+DEMAND and WHAMR! datasets. Meanwhile, we chose three types of data in the WHAMR! dataset to verify the ability of the D²Net on the tasks of denoising-only, dereverberation-only, and simultaneous denoising and dereverberation, respectively. Experimental results show that our proposed model outperforms the comparative models, and all achieve better performance on the tasks of simultaneous denoising and dereverberation, dereverberation-only, and denoising-only, while keeping a small number of network parameters.

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Tasks

DenoisingSpeech Enhancement

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Speech Enhancement VoiceBank + DEMAND D²Net CBAK 3.18 #17 of 42 Archive leaderboard report
Speech Enhancement VoiceBank + DEMAND D²Net COVL 3.92 #17 of 42 Archive leaderboard report
Speech Enhancement VoiceBank + DEMAND D²Net CSIG 4.63 #17 of 42 Archive leaderboard report
Speech Enhancement VoiceBank + DEMAND D²Net PESQ (wb) 3.27 #17 of 42 Archive leaderboard report
Speech Enhancement VoiceBank + DEMAND D²Net STOI 96 #17 of 42 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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