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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 551–600 of 982 papers

TitleStatusHype
Active Speech Enhancement: Active Speech Denoising Decliping and Deveraberation—0
A Curriculum Learning Method for Improved Noise Robustness in Automatic Speech Recognition—0
Adaptive Dereverberation, Noise and Interferer Reduction Using Sparse Weighted Linearly Constrained Minimum Power Beamforming—0
A Deep Representation Learning-based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencoder—0
A deep representation learning speech enhancement method using β-VAE—0
Artificial Intelligence for Cochlear Implants: Review of Strategies, Challenges, and Perspectives—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
Advances in Microphone Array Processing and Multichannel Speech Enhancement—0
AdVerb: Visually Guided Audio Dereverberation—0
Adversarial Feature Learning and Unsupervised Clustering based Speech Synthesis for Found Data with Acoustic and Textual Noise—0
Adversarial Feature-Mapping for Speech Enhancement—0
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition—0
多樣訊雜比之訓練語料於降噪自動編碼器其語音強化功能之初步研究 (A Preliminary Study of Various SNR-level Training Data in the Denoising Auto-encoder (DAE) Technique for Speech Enhancement) [In Chinese]—0
以軟體為基礎建構語音增強系統使用者介面 (Development of a software-based User-Interface of Speech Enhancement System) [In Chinese]—0
A Flow-Based Neural Network for Time Domain Speech Enhancement—0
A Framework for Unified Real-time Personalized and Non-Personalized Speech Enhancement—0
A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement—0
A Fused Deep Denoising Sound Coding Strategy for Bilateral Cochlear Implants—0
All Information is Necessary: Integrating Speech Positive and Negative Information by Contrastive Learning for Speech Enhancement—0
A Low-Power Streaming Speech Enhancement Accelerator For Edge Devices—0
Sequential Multi-Frame Neural Beamforming for Speech Separation and Enhancement—0
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network—0
A Model Compression Method with Matrix Product Operators for Speech Enhancement—0
A Monaural Speech Enhancement Method for Robust Small-Footprint Keyword Spotting—0
Multimodal Audio-Visual Information Fusion using Canonical-Correlated Graph Neural Network for Energy-Efficient Speech Enhancement—0
A Multiscale Autoencoder (MSAE) Framework for End-to-End Neural Network Speech Enhancement—0
Analysing Diffusion-based Generative Approaches versus Discriminative Approaches for Speech Restoration—0
Analysis of DNN Speech Signal Enhancement for Robust Speaker Recognition—0
Analysis of Noisy-target Training for DNN-based speech enhancement—0
Analyzing Upper Bounds on Mean Absolute Errors for Deep Neural Network Based Vector-to-Vector Regression—0
An Analysis of the Variance of Diffusion-based Speech Enhancement—0
An Empirical Study of Visual Features for DNN based Audio-Visual Speech Enhancement in Multi-talker Environments—0
An Empirical Study on the Impact of Positional Encoding in Transformer-based Monaural Speech Enhancement—0
An Ensemble SVM-based Approach for Voice Activity Detection—0
A network of deep neural networks for distant speech recognition—0
A Neural Acoustic Echo Canceller Optimized Using An Automatic Speech Recognizer And Large Scale Synthetic Data—0
A Neural Denoising Vocoder for Clean Waveform Generation from Noisy Mel-Spectrogram based on Amplitude and Phase Predictions—0
An experiment on an automated literature survey of data-driven speech enhancement methods—0
An Explicit Consistency-Preserving Loss Function for Phase Reconstruction and Speech Enhancement—0
An Exploration of Length Generalization in Transformer-Based Speech Enhancement—0
An Exploration of Task-decoupling on Two-stage Neural Post Filter for Real-time Personalized Acoustic Echo Cancellation—0
An Improved Measure of Musical Noise Based on Spectral Kurtosis—0
An improved uncertainty propagation method for robust i-vector based speaker recognition—0
An Investigation of Noise Robustness for Flow-Matching-Based Zero-Shot TTS—0
From KAN to GR-KAN: Advancing Speech Enhancement with KAN-Based Methodology—0
An Iterative Graph Spectral Subtraction Method for Speech Enhancement—0
A Noise-Aware Memory-Attention Network Architecture for Regression-Based Speech Enhancement—0
A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids—0
A Novel Speech Intelligibility Enhancement Model based on CanonicalCorrelation and Deep Learning—0
A Preliminary Study of the Application of Discrete Wavelet Transform Features in Conv-TasNet Speech Enhancement Model—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