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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 201–225 of 982 papers

Title	Date	Tasks	Status	Hype
Semi-Supervised Multichannel Speech Enhancement With a Deep Speech Prior	Oct 7, 2019	Speech Enhancement	CodeCode Available	1
INTERSPEECH 2021 ConferencingSpeech Challenge: Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing	Apr 2, 2021	Speech EnhancementTask 2	CodeCode Available	1
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks	Sep 1, 2017	DecoderMulti-Task Learning	—Unverified	0
Audio-Visual Speech Enhancement and Separation by Utilizing Multi-Modal Self-Supervised Embeddings	Oct 31, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
A network of deep neural networks for distant speech recognition	Mar 23, 2017	Distant Speech RecognitionSpeech Enhancement	—Unverified	0
Audio-visual multi-channel speech separation, dereverberation and recognition	Apr 5, 2022	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
An Ensemble SVM-based Approach for Voice Activity Detection	Feb 5, 2019	Action DetectionActivity Detection	—Unverified	0
Acoustic Structure Inverse Design and Optimization Using Deep Learning	Jan 29, 2021	Deep LearningSpeech Enhancement	—Unverified	0
Audio-visual End-to-end Multi-channel Speech Separation, Dereverberation and Recognition	Jul 6, 2023	Speech DereverberationSpeech Enhancement	—Unverified	0
Audio Recording Device Identification Based on Deep Learning	Feb 18, 2016	Deep LearningSpeech Enhancement	—Unverified	0
An Empirical Study on the Impact of Positional Encoding in Transformer-based Monaural Speech Enhancement	Jan 18, 2024	POSPosition	—Unverified	0
A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI	Mar 23, 2023	Speech EnhancementSpeech Synthesis	—Unverified	0
A two-step backward compatible fullband speech enhancement system	Jan 26, 2022	Speech EnhancementVocal Bursts Valence Prediction	—Unverified	0
An Empirical Study of Visual Features for DNN based Audio-Visual Speech Enhancement in Multi-talker Environments	Nov 9, 2020	Optical Flow EstimationSpeech Enhancement	—Unverified	0
Adversarial Joint Training with Self-Attention Mechanism for Robust End-to-End Speech Recognition	Apr 3, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Accelerating RNN-based Speech Enhancement on a Multi-Core MCU with Mixed FP16-INT8 Post-Training Quantization	Oct 14, 2022	QuantizationSpeech Enhancement	—Unverified	0
A Two-Stage Hierarchical Deep Filtering Framework for Real-Time Speech Enhancement	Jun 1, 2025	Speech Enhancement	—Unverified	0
A Two-Stage Framework in Cross-Spectrum Domain for Real-Time Speech Enhancement	Jan 19, 2024	Speech Enhancement	—Unverified	0
A Two-Stage Deep Representation Learning-Based Speech Enhancement Method Using Variational Autoencoder and Adversarial Training	Nov 16, 2022	Representation LearningSpeech Enhancement	—Unverified	0
A Two-stage Complex Network using Cycle-consistent Generative Adversarial Networks for Speech Enhancement	Sep 5, 2021	DenoisingSpeech Enhancement	—Unverified	0
An Analysis of the Variance of Diffusion-based Speech Enhancement	Feb 1, 2024	Speech Enhancement	—Unverified	0
Adversarial Feature-Mapping for Speech Enhancement	Sep 6, 2018	Speech Enhancement	—Unverified	0
Attention-Driven Multichannel Speech Enhancement in Moving Sound Source Scenarios	Dec 17, 2023	Speech Enhancement	—Unverified	0
Attention-based Speech Enhancement Using Human Quality Perception Modelling	Mar 23, 2023	Language ModelingLanguage Modelling	—Unverified	0
Analyzing Upper Bounds on Mean Absolute Errors for Deep Neural Network Based Vector-to-Vector Regression	Aug 4, 2020	Learning Theoryregression	—Unverified	0

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All datasets VoiceBank + DEMAND Deep Noise Suppression (DNS) Challenge CHiME-3 EARS-WHAM EasyCom DNS Challenge VB-DemandEx WHAMR!WSJ0 + DEMAND + RNNoise RealMAN VoiceBank+DEMAND DEMAND

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ROSE-CD(PESQ)	PESQ (wb)	3.99	—	Unverified
2	PESQetarian	PESQ (wb)	3.82	—	Unverified
3	Mamba-SEUNet L (+PCS)	PESQ (wb)	3.73	—	Unverified
4	Schrödinger bridge (PESQ loss)	PESQ (wb)	3.7	—	Unverified
5	SEMamba (+PCS)	PESQ (wb)	3.69	—	Unverified
6	ZipEnhancer (S, \lamba_6 = 0)	PESQ (wb)	3.63	—	Unverified
7	PrimeK-Net	PESQ (wb)	3.61	—	Unverified
8	ZipEnhancer (S, \lamba_6 = 0.2)	PESQ (wb)	3.61	—	Unverified
9	MP-SENet	PESQ (wb)	3.6	—	Unverified
10	PCS_CS_WAVLM	PESQ (wb)	3.54	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BSRNN-S + MGD	SI-SDR-WB	21.4	—	Unverified
2	DTLN	SI-SDR-WB	16.34	—	Unverified
3	Non-Real-Time MultiScale+	SI-SDR-WB	16.22	—	Unverified
4	ZipEnhancer (M)	PESQ-WB	3.81	—	Unverified
5	TF-Locoformer (M)	PESQ-WB	3.72	—	Unverified
6	ZipEnhancer (S)	PESQ-WB	3.69	—	Unverified
7	MambAttention	PESQ-WB	3.67	—	Unverified
8	MP-SENet	PESQ-WB	3.62	—	Unverified
9	xLSTM-SENet	PESQ-WB	3.59	—	Unverified
10	BSRNN-S + MRSD	PESQ-WB	3.53	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Inter-Channel Conv-TasNet	SDR	19.67	—	Unverified
2	CA Dense U-Net (Complex)	SDR	18.64	—	Unverified
3	Dense U-Net (Complex)	SDR	18.4	—	Unverified
4	Dense U-Net (Real)	SDR	16.86	—	Unverified
5	U-Net (Real)	SDR	15.97	—	Unverified
6	Noisy/unprocessed	SDR	6.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Schrödinger Bridge (PESQ loss)	PESQ-WB	3.09	—	Unverified
2	SGMSE+	PESQ-WB	2.5	—	Unverified
3	Demucs v4	PESQ-WB	2.37	—	Unverified
4	Schrödinger Bridge	PESQ-WB	2.33	—	Unverified
5	Conv-TasNet	PESQ-WB	2.31	—	Unverified
6	CDiffuSE	PESQ-WB	1.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ReVISE (ch2)	Audio Quality MOS	4.19	—	Unverified
2	ReVISE (bf)	Audio Quality MOS	4.11	—	Unverified
3	Demucs (ch2)	Audio Quality MOS	2.95	—	Unverified
4	Demucs (bf)	Audio Quality MOS	2.39	—	Unverified
5	MaxDI (Baseline)	PESQ	1.17	—	Unverified
6	DAJA (MVDR,HMA,1000) (Overlapped Speech)	SDR	-4.76	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ZipEnhancer (M)	PESQ-NB	4.08	—	Unverified
2	DCCRN-MC	PESQ-NB	3.21	—	Unverified
3	DCCRN-M	PESQ-NB	3.15	—	Unverified
4	DCCRN	PESQ-NB	3.04	—	Unverified
5	RNN-Modulation	PESQ-WB	2.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MambAttention	ESTOI	0.8	—	Unverified
2	SEMamba	ESTOI	0.8	—	Unverified
3	xLSTM-SENet	ESTOI	0.8	—	Unverified
4	MP-SENet	ESTOI	0.79	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SepFormer	PESQ	2.84	—	Unverified
2	DTLN	PESQ	2.23	—	Unverified
3	Unprocessed	PESQ	1.83	—	Unverified
4	Non-Real-Time MultiScale+	PESQ	1.52	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DCUNet-MC	PESQ-NB	3.44	—	Unverified
2	DCCRN-M	PESQ-NB	3.28	—	Unverified
3	DCUNet	PESQ-NB	3.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CleanMel-L-map	DNSMOS	3.82	—	Unverified
2	SpatialNet	DNSMOS BAK	3.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	rose_cd(PESQ )	PESQ	3.99	—	Unverified
2	ROSE-CD	PESQ	3.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Wave-U-Net	CBAK	3.24	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Audio-Visual concat-ref	PESQ	2.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SE-MelGAN	Audio Quality MOS	3.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeFT-AN	PESQ	3.01	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Audio-Visual concat-ref	PESQ	3.03	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SepFormer	PESQ	3.07	—	Unverified