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

Showing 651700 of 982 papers

TitleStatusHype
The NTNU Taiwanese ASR System for Formosa Speech Recognition Challenge 20200
Speech Denoising Without Clean Training Data: A Noise2Noise ApproachCode1
Phoneme-based Distribution Regularization for Speech Enhancement0
MetricGAN+: An Improved Version of MetricGAN for Speech EnhancementCode1
Real-time Streaming Wave-U-Net with Temporal Convolutions for Multichannel Speech Enhancement0
Personalized Speech Enhancement through Self-Supervised Data Augmentation and Purification0
Efficient Personalized Speech Enhancement through Self-Supervised Learning0
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition0
INTERSPEECH 2021 ConferencingSpeech Challenge: Towards Far-field Multi-Channel Speech Enhancement for Video ConferencingCode1
Deep Noise Suppression With Non-Intrusive PESQNet Supervision Enabling the Use of Real Training Data0
Time-domain Speech Enhancement with Generative Adversarial LearningCode0
TSTNN: Two-stage Transformer based Neural Network for Speech Enhancement in the Time Domain0
Towards Robust Speaker Verification with Target Speaker Enhancement0
Transformers with Competitive Ensembles of Independent Mechanisms0
Speech Enhancement Using Multi-Stage Self-Attentive Temporal Convolutional Networks0
A Robust Maximum Likelihood Distortionless Response Beamformer based on a Complex Generalized Gaussian Distribution0
Variational Autoencoder for Speech Enhancement with a Noise-Aware Encoder0
A Modulation-Domain Loss for Neural-Network-based Real-time Speech EnhancementCode1
Guided Variational Autoencoder for Speech Enhancement With a Supervised Classifier0
Speech enhancement with mixture-of-deep-experts with clean clustering pre-training0
An Investigation of End-to-End Models for Robust Speech RecognitionCode1
Real-time Monaural Speech Enhancement With Short-time Discrete Cosine Transform0
CDPAM: Contrastive learning for perceptual audio similarityCode1
Switching Variational Auto-Encoders for Noise-Agnostic Audio-visual Speech Enhancement0
Real-time Denoising and Dereverberation with Tiny Recurrent U-NetCode1
VSEGAN: Visual Speech Enhancement Generative Adversarial Network0
Monaural Speech Enhancement with Complex Convolutional Block Attention Module and Joint Time Frequency LossesCode2
High Fidelity Speech Regeneration with Application to Speech Enhancement0
Acoustic Structure Inverse Design and Optimization Using Deep Learning0
Speech Enhancement for Wake-Up-Word detection in Voice Assistants0
Towards efficient models for real-time deep noise suppression0
Noisy-target Training: A Training Strategy for DNN-based Speech Enhancement without Clean Speech0
AMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement0
Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement0
Neural Network-based Virtual Microphone Estimator0
Attention-based multi-task learning for speech-enhancement and speaker-identification in multi-speaker dialogue scenarioCode0
Visual Speech Enhancement Without A Real Visual StreamCode1
DCCRGAN: Deep Complex Convolution Recurrent Generator Adversarial Network for Speech Enhancement0
Interactive Speech and Noise Modeling for Speech Enhancement0
Speech Enhancement with Zero-Shot Model SelectionCode0
Group Communication with Context Codec for Lightweight Source SeparationCode1
Towards speech enhancement using a variational U-Net architecture0
Speaker Recognition Based on Deep Learning: An Overview0
Combining Spatial Clustering with LSTM Speech Models for Multichannel Speech Enhancement0
Enhancement of Spatial Clustering-Based Time-Frequency Masks using LSTM Neural Networks0
Deep Ad-hoc Beamforming Based on Speaker Extraction for Target-Dependent Speech Separation0
Speech Denoising with Auditory ModelsCode1
Deep Multi-Frame MVDR Filtering for Single-Microphone Speech EnhancementCode0
Ultra-Lightweight Speech Separation via Group Communication0
Multi-task single channel speech enhancement using speech presence probability as a secondary task training target0
Show:102550
← PrevPage 14 of 20Next →

Benchmark Results

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