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 251–300 of 982 papers

TitleStatusHype
Deep Residual Echo Suppression and Noise Reduction: A Multi-Input FCRN Approach in a Hybrid Speech Enhancement System—0
Deep Speech Enhancement for Reverberated and Noisy Signals using Wide Residual Networks—0
Deep Time Delay Neural Network for Speech Enhancement with Full Data Learning—0
Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures—0
DASB -- Discrete Audio and Speech Benchmark—0
AMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement—0
D²Net: A Denoising and Dereverberation Network Based on Two-branch Encoder and Dual-path Transformer—0
Cycle-Consistent Speech Enhancement—0
A Training Framework for Stereo-Aware Speech Enhancement using Deep Neural Networks—0
Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition—0
ctPuLSE: Close-Talk, and Pseudo-Label Based Far-Field, Speech Enhancement—0
Cross-domain Single-channel Speech Enhancement Model with Bi-projection Fusion Module for Noise-robust ASR—0
A time-domain nearfield frequency-invariant beamforming method—0
Cross-Attention is all you need: Real-Time Streaming Transformers for Personalised Speech Enhancement—0
Cross-attention conformer for context modeling in speech enhancement for ASR—0
AdVerb: Visually Guided Audio Dereverberation—0
Acoustic echo suppression using a learning-based multi-frame minimum variance distortionless response filter—0
A consolidated view of loss functions for supervised deep learning-based speech enhancement—0
Correlating Subword Articulation with Lip Shapes for Embedding Aware Audio-Visual Speech Enhancement—0
Cooperative Dual Attention for Audio-Visual Speech Enhancement with Facial Cues—0
ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion—0
Convolutional-Recurrent Neural Networks for Speech Enhancement—0
A Survey of Deep Learning for Complex Speech Spectrograms—0
A Multiscale Autoencoder (MSAE) Framework for End-to-End Neural Network Speech Enhancement—0
Convolutional Neural Network-based Speech Enhancement for Cochlear Implant Recipients—0
Convoifilter: A case study of doing cocktail party speech recognition—0
A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)—0
Controlling the Perceived Sound Quality for Dialogue Enhancement with Deep Learning—0
Continuous Modeling of the Denoising Process for Speech Enhancement Based on Deep Learning—0
Multimodal Audio-Visual Information Fusion using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement—0
Advances in Microphone Array Processing and Multichannel Speech Enhancement—0
Efficient High-Performance Bark-Scale Neural Network for Residual Echo and Noise Suppression—0
Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments—0
A Study of Incorporating Articulatory Movement Information in Speech Enhancement—0
Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy—0
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition—0
Advanced Clustering Techniques for Speech Signal Enhancement: A Review and Metanalysis of Fuzzy C-Means, K-Means, and Kernel Fuzzy C-Means Methods—0
Consistency-aware multi-channel speech enhancement using deep neural networks—0
Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification—0
A Statistically Principled and Computationally Efficient Approach to Speech Enhancement using Variational Autoencoders—0
Assessing the Generalization Gap of Learning-Based Speech Enhancement Systems in Noisy and Reverberant Environments—0
A Monaural Speech Enhancement Method for Robust Small-Footprint Keyword Spotting—0
A Dual-Staged Context Aggregation Method Towards Efficient End-To-End Speech Enhancement—0
Complex spectrogram enhancement by convolutional neural network with multi-metrics learning—0
Complex Spectral Mapping With Attention Based Convolution Recurrent Neural Network for Speech Enhancement—0
A Speech Production Model for Radar: Connecting Speech Acoustics with Radar-Measured Vibrations—0
Comparison of remote experiments using crowdsourcing and laboratory experiments on speech intelligibility—0
A Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning for Hearing-Assistive Technologies—0
A Model Compression Method with Matrix Product Operators for Speech Enhancement—0
Comparative Study between Adversarial Networks and Classical Techniques for 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