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Speech Enhancement

Speech Enhancement is a signal processing task that involves improving the quality of speech signals captured under noisy or degraded conditions. The goal of speech enhancement is to make speech signals clearer, more intelligible, and more pleasant to listen to, which can be used for various applications such as voice recognition, teleconferencing, and hearing aids. A representative Github project with online demo : ClearerVoice-Studio.

( Image credit: A Fully Convolutional Neural Network For Speech Enhancement )

Papers

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Showing 1–50 of 982 papers

TitleStatusHype
Autoregressive Speech Enhancement via Acoustic Tokens—0
P.808 Multilingual Speech Enhancement Testing: Approach and Results of URGENT 2025 Challenge—0
Speech Quality Assessment Model Based on Mixture of Experts: System-Level Performance Enhancement and Utterance-Level Challenge Analysis—0
Robust One-step Speech Enhancement via Consistency DistillationCode1
MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech EnhancementCode2
Frequency-Weighted Training Losses for Phoneme-Level DNN-based Speech Enhancement—0
EDNet: A Distortion-Agnostic Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Training—0
A Comparative Evaluation of Deep Learning Models for Speech Enhancement in Real-World Noisy Environments—0
Efficient Speech Enhancement via Embeddings from Pre-trained Generative AudioencodersCode2
Exploring Length Generalization For Transformer-based Speech Enhancement—0
French Listening Tests for the Assessment of Intelligibility, Quality, and Identity of Body-Conducted Speech Enhancement—0
Diffusion Buffer: Online Diffusion-based Speech Enhancement with Sub-Second Latency—0
Lessons Learned from the URGENT 2024 Speech Enhancement ChallengeCode0
A Two-Stage Hierarchical Deep Filtering Framework for Real-Time Speech Enhancement—0
A Composite Predictive-Generative Approach to Monaural Universal Speech Enhancement—0
Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You NeedCode0
Interspeech 2025 URGENT Speech Enhancement Challenge—0
DeepFilterGAN: A Full-band Real-time Speech Enhancement System with GAN-based Stochastic Regeneration—0
ARiSE: Auto-Regressive Multi-Channel Speech Enhancement—0
Study of Lightweight Transformer Architectures for Single-Channel Speech Enhancement—0
Model as Loss: A Self-Consistent Training Paradigm—0
Stack Less, Repeat More: A Block Reusing Approach for Progressive Speech Enhancement—0
A Lightweight Hybrid Dual Channel Speech Enhancement System under Low-SNR ConditionsCode2
FlowSE: Efficient and High-Quality Speech Enhancement via Flow MatchingCode2
Mel-McNet: A Mel-Scale Framework for Online Multichannel Speech EnhancementCode1
Training-Free Multi-Step Audio Source SeparationCode2
TS-URGENet: A Three-stage Universal Robust and Generalizable Speech Enhancement Network—0
Active Speech Enhancement: Active Speech Denoising Decliping and Deveraberation—0
Improving Noise Robustness of LLM-based Zero-shot TTS via Discrete Acoustic Token Denoising—0
A Semantic Information-based Hierarchical Speech Enhancement Method Using Factorized Codec and Diffusion Model—0
MDDM: A Multi-view Discriminative Enhanced Diffusion-based Model for Speech Enhancement—0
RoVo: Robust Voice Protection Against Unauthorized Speech Synthesis with Embedding-Level Perturbations—0
Unified Architecture and Unsupervised Speech Disentanglement for Speaker Embedding-Free Enrollment in Personalized Speech Enhancement—0
A Survey of Deep Learning for Complex Speech Spectrograms—0
Normalize Everything: A Preconditioned Magnitude-Preserving Architecture for Diffusion-Based Speech Enhancement—0
Robust Speech Recognition with Schrödinger Bridge-Based Speech Enhancement—0
SwinLip: An Efficient Visual Speech Encoder for Lip Reading Using Swin Transformer—0
CoGenAV: Versatile Audio-Visual Representation Learning via Contrastive-Generative SynchronizationCode2
How much to Dereverberate? Low-Latency Single-Channel Speech Enhancement in Distant Microphone Scenarios—0
Predicting speech intelligibility in older adults using the Gammachirp Envelope Similarity Index, GESI—0
DiTSE: High-Fidelity Generative Speech Enhancement via Latent Diffusion Transformers—0
Spatial-Filter-Bank-Based Neural Method for Multichannel Speech Enhancement—0
Magnitude-Phase Dual-Path Speech Enhancement Network based on Self-Supervised Embedding and Perceptual Contrast Stretch BoostingCode0
A Low-Power Streaming Speech Enhancement Accelerator For Edge Devices—0
Joint Spectrogram Separation and TDOA Estimation using Optimal Transport—0
HiFi-Stream: Streaming Speech Enhancement with Generative Adversarial NetworksCode1
A Speech Production Model for Radar: Connecting Speech Acoustics with Radar-Measured Vibrations—0
Variational Autoencoder for Personalized Pathological Speech Enhancement—0
Room Impulse Response Estimation through Optimal Mass Transport BarycentersCode0
FNSE-SBGAN: Far-field Speech Enhancement with Schrodinger Bridge and Generative Adversarial NetworksCode1
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All datasetsVoiceBank + DEMANDDeep Noise Suppression (DNS) ChallengeCHiME-3EARS-WHAMEasyComDNS ChallengeVB-DemandExWHAMR!WSJ0 + DEMAND + RNNoiseRealMANVoiceBank+DEMANDDEMAND

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ROSE-CD(PESQ)PESQ (wb)3.99—Unverified
2PESQetarianPESQ (wb)3.82—Unverified
3Mamba-SEUNet L (+PCS)PESQ (wb)3.73—Unverified
4Schrödinger bridge (PESQ loss)PESQ (wb)3.7—Unverified
5SEMamba (+PCS)PESQ (wb)3.69—Unverified
6ZipEnhancer (S, \lamba_6 = 0)PESQ (wb)3.63—Unverified
7PrimeK-NetPESQ (wb)3.61—Unverified
8ZipEnhancer (S, \lamba_6 = 0.2)PESQ (wb)3.61—Unverified
9MP-SENetPESQ (wb)3.6—Unverified
10PCS_CS_WAVLMPESQ (wb)3.54—Unverified
#ModelMetricClaimedVerifiedStatus
1BSRNN-S + MGDSI-SDR-WB21.4—Unverified
2DTLNSI-SDR-WB16.34—Unverified
3Non-Real-Time MultiScale+SI-SDR-WB16.22—Unverified
4ZipEnhancer (M)PESQ-WB3.81—Unverified
5TF-Locoformer (M)PESQ-WB3.72—Unverified
6ZipEnhancer (S)PESQ-WB3.69—Unverified
7MambAttentionPESQ-WB3.67—Unverified
8MP-SENetPESQ-WB3.62—Unverified
9xLSTM-SENetPESQ-WB3.59—Unverified
10BSRNN-S + MRSDPESQ-WB3.53—Unverified
#ModelMetricClaimedVerifiedStatus
1Inter-Channel Conv-TasNetSDR19.67—Unverified
2CA Dense U-Net (Complex)SDR18.64—Unverified
3Dense U-Net (Complex)SDR18.4—Unverified
4Dense U-Net (Real)SDR16.86—Unverified
5U-Net (Real)SDR15.97—Unverified
6Noisy/unprocessedSDR6.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Schrödinger Bridge (PESQ loss)PESQ-WB3.09—Unverified
2SGMSE+PESQ-WB2.5—Unverified
3Demucs v4PESQ-WB2.37—Unverified
4Schrödinger BridgePESQ-WB2.33—Unverified
5Conv-TasNetPESQ-WB2.31—Unverified
6CDiffuSEPESQ-WB1.6—Unverified
#ModelMetricClaimedVerifiedStatus
1ReVISE (ch2)Audio Quality MOS4.19—Unverified
2ReVISE (bf)Audio Quality MOS4.11—Unverified
3Demucs (ch2)Audio Quality MOS2.95—Unverified
4Demucs (bf)Audio Quality MOS2.39—Unverified
5MaxDI (Baseline)PESQ1.17—Unverified
6DAJA (MVDR,HMA,1000) (Overlapped Speech)SDR-4.76—Unverified
#ModelMetricClaimedVerifiedStatus
1ZipEnhancer (M)PESQ-NB4.08—Unverified
2DCCRN-MCPESQ-NB3.21—Unverified
3DCCRN-MPESQ-NB3.15—Unverified
4DCCRNPESQ-NB3.04—Unverified
5RNN-ModulationPESQ-WB2.75—Unverified
#ModelMetricClaimedVerifiedStatus
1MambAttentionESTOI0.8—Unverified
2SEMambaESTOI0.8—Unverified
3xLSTM-SENetESTOI0.8—Unverified
4MP-SENetESTOI0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1SepFormerPESQ2.84—Unverified
2DTLNPESQ2.23—Unverified
3UnprocessedPESQ1.83—Unverified
4Non-Real-Time MultiScale+PESQ1.52—Unverified
#ModelMetricClaimedVerifiedStatus
1DCUNet-MCPESQ-NB3.44—Unverified
2DCCRN-MPESQ-NB3.28—Unverified
3DCUNetPESQ-NB3.25—Unverified
#ModelMetricClaimedVerifiedStatus
1CleanMel-L-mapDNSMOS3.82—Unverified
2SpatialNetDNSMOS BAK3.43—Unverified
#ModelMetricClaimedVerifiedStatus
1rose_cd(PESQ )PESQ3.99—Unverified
2ROSE-CDPESQ3.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Wave-U-NetCBAK3.24—Unverified
#ModelMetricClaimedVerifiedStatus
1Audio-Visual concat-refPESQ2.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SE-MelGANAudio Quality MOS3.1—Unverified
#ModelMetricClaimedVerifiedStatus
1DeFT-ANPESQ3.01—Unverified
#ModelMetricClaimedVerifiedStatus
1Audio-Visual concat-refPESQ3.03—Unverified
#ModelMetricClaimedVerifiedStatus
1SepFormerPESQ3.07—Unverified