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 401450 of 982 papers

TitleStatusHype
Enhancement and Recognition of Reverberant and Noisy Speech by Extending Its Coherence0
Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization0
Guided Speech Enhancement Network0
Guided Variational Autoencoder for Speech Enhancement With a Supervised Classifier0
Harmonic and non-Harmonic Based Noisy Reverberant Speech Enhancement in Time Domain0
Harmonic enhancement using learnable comb filter for light-weight full-band speech enhancement model0
Bridging the Gap Between Monaural Speech Enhancement and Recognition with Distortion-Independent Acoustic Modeling0
Helsinki Speech Challenge 20240
Heterogeneous Space Fusion and Dual-Dimension Attention: A New Paradigm for Speech Enhancement0
End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks0
Hidden-Markov-Model Based Speech Enhancement0
End-to-End Neural Speech Coding for Real-Time Communications0
End-to-End Model for Speech Enhancement by Consistent Spectrogram Masking0
Bridging The Multi-Modality Gaps of Audio, Visual and Linguistic for Speech Enhancement0
A Novel Frame Structure for Cloud-Based Audio-Visual Speech Enhancement in Multimodal Hearing-aids0
A Composite Predictive-Generative Approach to Monaural Universal Speech Enhancement0
High-quality Speech Synthesis Using Super-resolution Mel-Spectrogram0
Controlling the Perceived Sound Quality for Dialogue Enhancement with Deep Learning0
End-to-End Integration of Speech Recognition, Speech Enhancement, and Self-Supervised Learning Representation0
How Bad Are Artifacts?: Analyzing the Impact of Speech Enhancement Errors on ASR0
How does end-to-end speech recognition training impact speech enhancement artifacts?0
How much to Dereverberate? Low-Latency Single-Channel Speech Enhancement in Distant Microphone Scenarios0
End-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression0
Human Listening and Live Captioning: Multi-Task Training for Speech Enhancement0
Employing low-pass filtered temporal speech features for the training of ideal ratio mask in speech enhancement0
EMGSE: Acoustic/EMG Fusion for Multimodal Speech Enhancement0
Breaking the trade-off in personalized speech enhancement with cross-task knowledge distillation0
ELAICHI: Enhancing Low-resource TTS by Addressing Infrequent and Low-frequency Character Bigrams0
Egocentric Audio-Visual Noise Suppression0
Improved Normalizing Flow-Based Speech Enhancement using an All-pole Gammatone Filterbank for Conditional Input Representation0
Cross-attention conformer for context modeling in speech enhancement for ASR0
Improved Speech Enhancement with the Wave-U-Net0
Improving Character Error Rate Is Not Equal to Having Clean Speech: Speech Enhancement for ASR Systems with Black-box Acoustic Models0
Cross-Attention is all you need: Real-Time Streaming Transformers for Personalised Speech Enhancement0
Improving Dual-Microphone Speech Enhancement by Learning Cross-Channel Features with Multi-Head Attention0
Boosting Objective Scores of a Speech Enhancement Model by MetricGAN Post-processing0
Improving noise robust automatic speech recognition with single-channel time-domain enhancement network0
Improving Noise Robustness of Contrastive Speech Representation Learning with Speech Reconstruction0
Improving Noise Robustness of LLM-based Zero-shot TTS via Discrete Acoustic Token Denoising0
Efficient Transformer-based Speech Enhancement Using Long Frames and STFT Magnitudes0
Improving Perceptual Quality, Intelligibility, and Acoustics on VoIP Platforms0
Improving spatial cues for hearables using a parameterized binaural CDR estimator0
Efficient Trainable Front-Ends for Neural Speech Enhancement0
Boosting Noise Robustness of Acoustic Model via Deep Adversarial Training0
Improving the Intent Classification accuracy in Noisy Environment0
Improving Visual Speech Enhancement Network by Learning Audio-visual Affinity with Multi-head Attention0
A Novel Speech Intelligibility Enhancement Model based on CanonicalCorrelation and Deep Learning0
Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization0
Incorporating Real-world Noisy Speech in Neural-network-based Speech Enhancement Systems0
A Bayesian Permutation training deep representation learning method for speech enhancement with variational autoencoder0
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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