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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 601–650 of 982 papers

TitleStatusHype
A Recurrent Variational Autoencoder for Speech Enhancement—0
ARiSE: Auto-Regressive Multi-Channel Speech Enhancement—0
A Robust Maximum Likelihood Distortionless Response Beamformer based on a Complex Generalized Gaussian Distribution—0
Array Configuration-Agnostic Personalized Speech Enhancement using Long-Short-Term Spatial Coherence—0
Array Configuration-Agnostic Personal Voice Activity Detection Based on Spatial Coherence—0
Array Geometry-Robust Attention-Based Neural Beamformer for Moving Speakers—0
Artifact-free Sound Quality in DNN-based Closed-loop Systems for Audio Processing—0
A scalable noisy speech dataset and online subjective test framework—0
A Semantic Information-based Hierarchical Speech Enhancement Method Using Factorized Codec and Diffusion Model—0
A Single Speech Enhancement Model Unifying Dereverberation, Denoising, Speaker Counting, Separation, and Extraction—0
語音增強基於小腦模型控制器(A Speech Enhancement System Based on Cerebellar Model Articulation Controller) [In Chinese]—0
A Speech Intelligibility Enhancement Model based on Canonical Correlation and Deep Learning for Hearing-Assistive Technologies—0
A Speech Production Model for Radar: Connecting Speech Acoustics with Radar-Measured Vibrations—0
Assessing the Generalization Gap of Learning-Based Speech Enhancement Systems in Noisy and Reverberant Environments—0
A Statistically Principled and Computationally Efficient Approach to Speech Enhancement using Variational Autoencoders—0
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition—0
A Study of Incorporating Articulatory Movement Information in Speech Enhancement—0
A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)—0
A Survey of Deep Learning for Complex Speech Spectrograms—0
A time-domain nearfield frequency-invariant beamforming method—0
A Training Framework for Stereo-Aware Speech Enhancement using Deep Neural Networks—0
AMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement—0
Attention-based Speech Enhancement Using Human Quality Perception Modelling—0
Attention-Driven Multichannel Speech Enhancement in Moving Sound Source Scenarios—0
A Two-stage Complex Network using Cycle-consistent Generative Adversarial Networks for Speech Enhancement—0
A Two-Stage Deep Representation Learning-Based Speech Enhancement Method Using Variational Autoencoder and Adversarial Training—0
A Two-Stage Framework in Cross-Spectrum Domain for Real-Time Speech Enhancement—0
A Two-Stage Hierarchical Deep Filtering Framework for Real-Time Speech Enhancement—0
A two-step backward compatible fullband speech enhancement system—0
A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI—0
Audio Recording Device Identification Based on Deep Learning—0
Audio-visual End-to-end Multi-channel Speech Separation, Dereverberation and Recognition—0
Audio-visual multi-channel speech separation, dereverberation and recognition—0
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
Audio-Visual Speech Enhancement in Noisy Environments via Emotion-Based Contextual Cues—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
Audio-visual Speech Enhancement Using Conditional Variational Auto-Encoders—0
Audio-Visual Speech Enhancement Using Self-supervised Learning to Improve Speech Intelligibility in Cochlear Implant Simulations—0
Audio-Visual Speech Enhancement With Selective Off-Screen Speech Extraction—0
Audio-visual speech enhancement with a deep Kalman filter generative model—0
Audio-Visual Speech Enhancement with Score-Based Generative Models—0
A Unified Deep Learning Framework for Short-Duration Speaker Verification in Adverse Environments—0
A unified multichannel far-field speech recognition system: combining neural beamforming with attention based end-to-end model—0
A Universally-Deployable ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement, and Voice Separation—0
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data—0
Autoregressive Speech Enhancement via Acoustic Tokens—0
AV2Wav: Diffusion-Based Re-synthesis from Continuous Self-supervised Features for Audio-Visual Speech Enhancement—0
AV Speech Enhancement Challenge using a Real Noisy Corpus—0
Batch-normalized joint training for DNN-based distant speech recognition—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