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 301–350 of 982 papers

TitleStatusHype
Ultra-Low Latency Speech Enhancement - A Comprehensive Study—0
Leveraging Joint Spectral and Spatial Learning with MAMBA for Multichannel Speech Enhancement—0
Investigating Training Objectives for Generative Speech EnhancementCode0
TCG CREST System Description for the Second DISPLACE Challenge—0
Rethinking Mamba in Speech Processing by Self-Supervised Models—0
DeWinder: Single-Channel Wind Noise Reduction using Ultrasound Sensing—0
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
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
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
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
Direction of Arrival Correction through Speech Quality FeedbackCode0
One-Shot Distributed Node-Specific Signal Estimation with Non-Overlapping Latent Subspaces in Acoustic Sensor Networks—0
ctPuLSE: Close-Talk, and Pseudo-Label Based Far-Field, Speech Enhancement—0
Speech Bandwidth Expansion Via High Fidelity Generative Adversarial Networks—0
Schrödinger Bridge for Generative Speech Enhancement—0
Wideband Relative Transfer Function (RTF) Estimation Exploiting Frequency CorrelationsCode0
RT-LA-VocE: Real-Time Low-SNR Audio-Visual Speech Enhancement—0
Unsupervised Face-Masked Speech Enhancement Using Generative Adversarial Networks With Human-in-the-Loop Assessment Metrics—0
Open-Source Conversational AI with SpeechBrain 1.0—0
DASB -- Discrete Audio and Speech Benchmark—0
Diffusion-based Generative Modeling with Discriminative Guidance for Streamable Speech Enhancement—0
Spatially constrained vs. unconstrained filtering in neural spatiospectral filters for multichannel speech enhancement—0
An Exploration of Length Generalization in Transformer-Based Speech Enhancement—0
Personalized Speech Enhancement Without a Separate Speaker Embedding Model—0
FlowAVSE: Efficient Audio-Visual Speech Enhancement with Conditional Flow Matching—0
Comparative Analysis of Personalized Voice Activity Detection Systems: Assessing Real-World Effectiveness—0
Pre-training Feature Guided Diffusion Model for Speech Enhancement—0
The Effect of Training Dataset Size on Discriminative and Diffusion-Based Speech Enhancement Systems—0
Thunder : Unified Regression-Diffusion Speech Enhancement with a Single Reverse Step using Brownian Bridge—0
An Investigation of Noise Robustness for Flow-Matching-Based Zero-Shot TTS—0
URGENT Challenge: Universality, Robustness, and Generalizability For Speech Enhancement—0
Helsinki Speech Challenge 2024—0
Flexible Multichannel Speech Enhancement for Noise-Robust Frontend—0
PLDNet: PLD-Guided Lightweight Deep Network Boosted by Efficient Attention for Handheld Dual-Microphone Speech Enhancement—0
Reference Channel Selection by Multi-Channel Masking for End-to-End Multi-Channel Speech Enhancement—0
The PESQetarian: On the Relevance of Goodhart's Law for Speech Enhancement—0
Speech enhancement deep-learning architecture for efficient edge processing—0
Non-autoregressive real-time Accent Conversion model with voice cloning—0
Monaural speech enhancement on drone via Adapter based transfer learning—0
Building a Luganda Text-to-Speech Model From Crowdsourced Data—0
Evaluating Speech Enhancement Systems Through Listening Effort—0
Real-time multichannel deep speech enhancement in hearing aids: Comparing monaural and binaural processing in complex acoustic scenarios—0
TRAMBA: A Hybrid Transformer and Mamba Architecture for Practical Audio and Bone Conduction Speech Super Resolution and Enhancement on Mobile and Wearable Platforms—0
Deep low-latency joint speech transmission and enhancement over a gaussian channel—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