⭐博客推荐：https://www.cnblogs.com/LXP-Never/category/2067387.html
1、⭐FULLSUBNET: A FULL-BAND AND SUB-BAND FUSION MODEL FOR REAL-TIME SINGLE-CHANNEL SPEECH ENHANCEMENT.2021. 【PDF】.【code】
2、Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for Single-channel Speech.2023. 【PDF】.【code】
3、Deep Subband Network for Joint Suppression of Echo, Noise and Reverberation in Real-Time Fullband Speech Communication.2023. 【PDF】.【code】
4、Lightweight Full-band and Sub-band Fusion Network for Real Time Speech Enhancement.2023. 【PDF】.
5、⭐FullSubNet+: Channel Attention Fullsubnet with Complex Spectrograms for Speech Enhancement.2022. 【PDF】.
1、⭐DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement. 2020.【PDF】【code】.
2、DCCRN+: Channel-wise Subband DCCRN with SNR Estimation for Speech Enhancement. 2021.【PDF】.
3、S-DCCRN: SUPER WIDE BAND DCCRN WITH LEARNABLE COMPLEX FEATURE FOR SPEECH ENHANCEMENT. 2021.【PDF】.
4、FRCRN: BOOSTING FEATURE REPRESENTATION USING FREQUENCY RECURRENCE FOR MONAURAL SPEECH ENHANCEMENT. 2022.【PDF】.
5、FB-MSTCN: A FULL-BAND SINGLE-CHANNEL SPEECH ENHANCEMENT METHOD BASED ON MULTI-SCALE TEMPORAL CONVOLUTIONAL NETWORK. 2022.【PDF】.
1、T-GSA: Transformer with Gaussian-Weighted Self-Attention for Speech Enhancement. 2020.【PDF】.
2、TSTNN: TWO-STAGE TRANSFORMER BASED NEURAL NETWORK FOR SPEECH ENHANCEMENT IN THE TIME DOMAIN. 2021.【PDF】.
3、⭐UFORMER: A UNET BASED DILATED COMPLEX & REAL DUAL-PATH CONFORMER NETWORK FOR SIMULTANEOUS SPEECH ENHANCEMENT AND DEREVERBERATION. 2022.【PDF】.
1、Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation. 2020.【PDF】.【code】
2、DPCRN: Dual-Path Convolution Recurrent Network for Single Channel Speech Enhancement. 2021.【PDF】.
3、⭐DPT-FSNET: DUAL-PATH TRANSFORMER BASED FULL-BAND AND SUB-BAND FUSION NETWORK FOR SPEECH ENHANCEMENT . 2022.【PDF】.
1、MUSE: Flexible Voiceprint Receptive Fields and Multi-Path Fusion Enhanced Taylor Transformer for U-Net-based Speech Enhancement. 2024.【PDF】.【code】
2、Mel-FullSubNet: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR. 2024.【PDF】.
3、SICRN: Advancing Speech Enhancement through State Space Model and Inplace Convolution Techniques. 2024ICASSP 【PDF】.
4、The PESQetarian: On the Relevance of Goodhart's Law for Speech Enhancement. 2024INTERSPEECH 【PDF】.
5、An Exploration of Length Generalization in Transformer-Based Speech Enhancement. 2024INTERSPEECH 【PDF】.
6、PLDNet: PLD-Guided Lightweight Deep Network Boosted by Efficient Attention for Handheld Dual-Microphone Speech Enhancement. 2024INTERSPEECH 【PDF】.
7、Reference Channel Selection by Multi-Channel Masking for End-to-End Multi-Channel Speech Enhancement. 2024 【PDF】.
8、⭐A Two-Stage Framework in Cross-Spectrum Domain for Real-Time Speech Enhancement. 2024ICASSP 【PDF】.
9、⭐On real-time multi-stage speech enhancement systems. 2024ICASSP 【PDF】.
10、⭐GTCRN: A Speech Enhancement Model Requiring Ultralow Computational Resources. 2024ICASSP 【PDF】.
11、⭐D2Former: a Fully Complex Dual-Path Dual-Decoder Conformer Network Using Joint Complex Masking and Complex Spectral Mapping for Monaural Speech Enhancement. 2023ICASSP 【PDF】.
1、⭐Real Time Speech Enhancement in the Waveform Domain. 2020.【PDF】.【code】.
2、Glance and gaze: A collaborative learning framework for single-channel speech enhancement.
3、SPEECH DENOISING IN THE WAVEFORM DOMAIN WITH SELF-ATTENTION.
4、Learning Complex Spectral Mapping With Gated Convolutional Recurrent Networks for Monaural Speech Enhancement.
5、Inter-Subnet: Speech Enhancement with Subband Interaction.
6、Speech Enhancement with Fullband-Subband Cross-Attention Network.