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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 51–100 of 982 papers

TitleStatusHype
Linguistic Knowledge Transfer Learning for Speech Enhancement—0
ProSE: Diffusion Priors for Speech Enhancement—0
UL-UNAS: Ultra-Lightweight U-Nets for Real-Time Speech Enhancement via Network Architecture SearchCode2
LLaSE-G1: Incentivizing Generalization Capability for LLaMA-based Speech EnhancementCode2
CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASRCode2
PrimeK-Net: Multi-scale Spectral Learning via Group Prime-Kernel Convolutional Neural Networks for Single Channel Speech EnhancementCode1
Enhancing Speech Quality through the Integration of BGRU and Transformer Architectures—0
Speech Enhancement Using Continuous Embeddings of Neural Audio Codec—0
Adaptive Convolution for CNN-based Speech Enhancement ModelsCode1
LMFCA-Net: A Lightweight Model for Multi-Channel Speech Enhancement with Efficient Narrow-Band and Cross-Band Attention—0
TAPS: Throat and Acoustic Paired Speech Dataset for Deep Learning-Based Speech Enhancement—0
Microphone Array Geometry Independent Multi-Talker Distant ASR: NTT System for the DASR Task of the CHiME-8 Challenge—0
Advances in Microphone Array Processing and Multichannel Speech Enhancement—0
GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling—0
Metis: A Foundation Speech Generation Model with Masked Generative Pre-trainingCode9
Learning-based A Posteriori Speech Presence Probability Estimation and Applications—0
Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancement—0
Generative Data Augmentation Challenge: Zero-Shot Speech Synthesis for Personalized Speech Enhancement—0
UP-Cycle-SENet: Unpaired Phase-aware Speech Enhancement Using Deep Complex Cycle Adversarial Networks—0
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor ContractionsCode0
Speech Enhancement with Overlapped-Frame Information Fusion and Causal Self-AttentionCode0
SEF-PNet: Speaker Encoder-Free Personalized Speech Enhancement with Local and Global Contexts AggregationCode1
DFingerNet: Noise-Adaptive Speech Enhancement for Hearing Aids—0
Microphone Array Signal Processing and Deep Learning for Speech Enhancement—0
Multi-modal Speech Enhancement with Limited Electromyography Channels—0
Estimation and Restoration of Unknown Nonlinear Distortion using DiffusionCode0
xLSTM-SENet: xLSTM for Single-Channel Speech EnhancementCode2
AnCoGen: Analysis, Control and Generation of Speech with a Masked AutoencoderCode1
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
Artifact-free Sound Quality in DNN-based Closed-loop Systems for Audio Processing—0
Causal Speech Enhancement with Predicting Semantics based on Quantized Self-supervised Learning Features—0
Neural Directed Speech Enhancement with Dual Microphone Array in High Noise Scenario—0
From KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based Methodology—0
Time-Graph Frequency Representation with Singular Value Decomposition for Neural Speech EnhancementCode0
Scalable Speech Enhancement with Dynamic Channel Pruning—0
Mamba-SEUNet: Mamba UNet for Monaural Speech EnhancementCode2
Scale This, Not That: Investigating Key Dataset Attributes for Efficient Speech Enhancement Scaling—0
Investigating the Effects of Diffusion-based Conditional Generative Speech Models Used for Speech Enhancement on Dysarthric Speech—0
Evaluating the Impact of Discriminative and Generative E2E Speech Enhancement Models on Syllable Stress Preservation—0
TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch—0
Source Separation & Automatic Transcription for MusicCode1
SALMONN-omni: A Codec-free LLM for Full-duplex Speech Understanding and Generation—0
Towards Advanced Speech Signal Processing: A Statistical Perspective on Convolution-Based Architectures and its Applications—0
GhostRNN: Reducing State Redundancy in RNN with Cheap Operations—0
A Neural Denoising Vocoder for Clean Waveform Generation from Noisy Mel-Spectrogram based on Amplitude and Phase Predictions—0
Explainable DNN-based Beamformer with PostfilterCode1
SAV-SE: Scene-aware Audio-Visual Speech Enhancement with Selective State Space Model—0
DCF-DS: Deep Cascade Fusion of Diarization and Separation for Speech Recognition under Realistic Single-Channel Conditions—0
Selective State Space Model for Monaural Speech Enhancement—0
Modulating State Space Model with SlowFast Framework for Compute-Efficient Ultra Low-Latency Speech Enhancement—0
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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