SOTAVerified

Speech Denoising

Obtain the clean speech of the target speaker by suppressing the background noise. Recent representative github platform ClearerVoice-Studio

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 65 papers

TitleStatusHype
FRA-RIR: Fast Random Approximation of the Image-source MethodCode2
Speech Dereverberation with A Reverberation Time Shortening Target—0
VoiceFixer: A Unified Framework for High-Fidelity Speech RestorationCode3
FB-MSTCN: A Full-Band Single-Channel Speech Enhancement Method Based on Multi-Scale Temporal Convolutional Network—0
The PCG-AIID System for L3DAS22 Challenge: MIMO and MISO convolutional recurrent Network for Multi Channel Speech Enhancement and Speech Recognition—0
Multi-Channel Speech Denoising for Machine Ears—0
Speech Denoising in the Waveform Domain with Self-AttentionCode2
Task-specific Optimization of Virtual Channel Linear Prediction-based Speech Dereverberation Front-End for Far-Field Speaker VerificationCode0
S-DCCRN: Super Wide Band DCCRN with learnable complex feature for speech enhancement—0
Self-Supervised Speech Denoising Using Only Noisy Audio SignalsCode1
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech ProcessingCode3
Spark Deficient Gabor Frames for Inverse Problems—0
Perceptual-based deep-learning denoiser as a defense against adversarial attacks on ASR systems—0
Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization—0
Zero-Shot Personalized Speech Enhancement through Speaker-Informed Model Selection—0
Speech Denoising Without Clean Training Data: A Noise2Noise ApproachCode1
Learning robust speech representation with an articulatory-regularized variational autoencoder—0
TSTNN: Two-stage Transformer based Neural Network for Speech Enhancement in the Time Domain—0
A Modulation-Domain Loss for Neural-Network-based Real-time Speech EnhancementCode1
Monaural Speech Enhancement with Complex Convolutional Block Attention Module and Joint Time Frequency LossesCode2
Visual Speech Enhancement Without A Real Visual StreamCode1
Speech Denoising with Auditory ModelsCode1
Improving Speech Enhancement Performance by Leveraging Contextual Broad Phonetic Class Information—0
Perceptual Loss based Speech Denoising with an ensemble of Audio Pattern Recognition and Self-Supervised ModelsCode0
Listening to Sounds of Silence for Speech DenoisingCode1
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All datasetsLRS2+VGGSoundLRS3+VGGSound

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CBAK2.41—Unverified
#ModelMetricClaimedVerifiedStatus
1CBAK2.47—Unverified