SOTAVerified

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 101–150 of 982 papers

TitleStatusHype
Task-Aware Unified Source Separation—0
Run-Time Adaptation of Neural Beamforming for Robust Speech Dereverberation and Denoising—0
Simultaneous Diarization and Separation of Meetings through the Integration of Statistical Mixture Models—0
ELAICHI: Enhancing Low-resource TTS by Addressing Infrequent and Low-frequency Character Bigrams—0
Using RLHF to align speech enhancement approaches to mean-opinion quality scores—0
GAN-Based Speech Enhancement for Low SNR Using Latent Feature Conditioning—0
FINALLY: fast and universal speech enhancement with studio-like quality—0
Towards Ultra-Low-Power Neuromorphic Speech Enhancement with Spiking-FullSubNetCode2
RelUNet: Relative Channel Fusion U-Net for Multichannel Speech Enhancement—0
Diffusion-based Unsupervised Audio-visual Speech Enhancement—0
Restorative Speech Enhancement: A Progressive Approach Using SE and Codec Modules—0
SonicSim: A customizable simulation platform for speech processing in moving sound source scenariosCode3
Advanced Clustering Techniques for Speech Signal Enhancement: A Review and Metanalysis of Fuzzy C-Means, K-Means, and Kernel Fuzzy C-Means Methods—0
Speech Boosting: Low-Latency Live Speech Enhancement for TWS Earbuds—0
Towards Sub-millisecond Latency Real-Time Speech Enhancement Models on Hearables—0
MC-SEMamba: A Simple Multi-channel Extension of SEMamba—0
An Explicit Consistency-Preserving Loss Function for Phase Reconstruction and Speech Enhancement—0
Robust Audio-Visual Speech Enhancement: Correcting Misassignments in Complex Environments with Advanced Post-Processing—0
Self-Supervised Audio-Visual Soundscape Stylization—0
LiSenNet: Lightweight Sub-band and Dual-Path Modeling for Real-Time Speech EnhancementCode2
Geometry-Constrained EEG Channel Selection for Brain-Assisted Speech Enhancement—0
Speech-Declipping Transformer with Complex Spectrogram and Learnerble Temporal Features—0
A Lightweight and Real-Time Binaural Speech Enhancement Model with Spatial Cues PreservationCode1
Dense-TSNet: Dense Connected Two-Stage Structure for Ultra-Lightweight Speech Enhancement—0
High-Resolution Speech Restoration with Latent Diffusion ModelCode0
TCG CREST System Description for the Second DISPLACE Challenge—0
Investigating Training Objectives for Generative Speech EnhancementCode0
Leveraging Joint Spectral and Spatial Learning with MAMBA for Multichannel Speech Enhancement—0
Ultra-Low Latency Speech Enhancement - A Comprehensive Study—0
Apollo: Band-sequence Modeling for High-Quality Audio RestorationCode3
Rethinking Mamba in Speech Processing by Self-Supervised Models—0
DeWinder: Single-Channel Wind Noise Reduction using Ultrasound Sensing—0
IndicVoices-R: Unlocking a Massive Multilingual Multi-speaker Speech Corpus for Scaling Indian TTSCode2
TF-Mamba: A Time-Frequency Network for Sound Source Localization—0
Diffusion-based Speech Enhancement with Schrödinger Bridge and Symmetric Noise Schedule—0
aTENNuate: Optimized Real-time Speech Enhancement with Deep SSMs on Raw Audio—0
LSTMSE-Net: Long Short Term Speech Enhancement Network for Audio-visual Speech EnhancementCode1
Effective Noise-aware Data Simulation for Domain-adaptive Speech Enhancement Leveraging Dynamic Stochastic PerturbationCode0
Progressive Residual Extraction based Pre-training for Speech Representation Learning—0
Hold Me Tight: Stable Encoder-Decoder Design for Speech EnhancementCode1
Spectral Masking with Explicit Time-Context Windowing for Neural Network-Based Monaural Speech Enhancement—0
Dynamic Gated Recurrent Neural Network for Compute-efficient Speech Enhancement—0
DPSNN: Spiking Neural Network for Low-Latency Streaming Speech Enhancement—0
Direction of Arrival Correction through Speech Quality FeedbackCode0
Heterogeneous Space Fusion and Dual-Dimension Attention: A New Paradigm for Speech Enhancement—0
BSS-CFFMA: Cross-Domain Feature Fusion and Multi-Attention Speech Enhancement Network based on Self-Supervised EmbeddingCode0
One-Shot Distributed Node-Specific Signal Estimation with Non-Overlapping Latent Subspaces in Acoustic Sensor Networks—0
TF-Locoformer: Transformer with Local Modeling by Convolution for Speech Separation and EnhancementCode2
ctPuLSE: Close-Talk, and Pseudo-Label Based Far-Field, Speech Enhancement—0
Speech Bandwidth Expansion Via High Fidelity Generative Adversarial Networks—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