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 676–700 of 982 papers

Title	Date	Tasks	Status
Cold Diffusion for Speech Enhancement	Nov 4, 2022	Speech Enhancement	—Unverified
Collaborative Deep Learning for Speech Enhancement: A Run-Time Model Selection Method Using Autoencoders	May 29, 2017	Model SelectionSpeech Enhancement	—Unverified
Combining Spatial Clustering with LSTM Speech Models for Multichannel Speech Enhancement	Dec 2, 2020	ClusteringSpeech Enhancement	—Unverified
Comparative Analysis of Personalized Voice Activity Detection Systems: Assessing Real-World Effectiveness	Jun 12, 2024	Action DetectionActivity Detection	—Unverified
Comparative Study between Adversarial Networks and Classical Techniques for Speech Enhancement	Oct 21, 2019	Speech Enhancement	—Unverified
Comparison of remote experiments using crowdsourcing and laboratory experiments on speech intelligibility	Apr 17, 2021	Speech Enhancement	—Unverified
Complex Spectral Mapping With Attention Based Convolution Recurrent Neural Network for Speech Enhancement	Apr 12, 2021	DecoderSpeech Enhancement	—Unverified
Complex spectrogram enhancement by convolutional neural network with multi-metrics learning	Apr 27, 2017	Speech Enhancement	—Unverified
Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification	Sep 6, 2017	Speaker VerificationSpeech Enhancement	—Unverified
Consistency-aware multi-channel speech enhancement using deep neural networks	Feb 14, 2020	Speech Enhancement	—Unverified
Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy	Feb 16, 2018	DecoderLanguage Modeling	—Unverified
Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments	Aug 28, 2018	Lip ReadingSpeech Enhancement	—Unverified
Continuous Modeling of the Denoising Process for Speech Enhancement Based on Deep Learning	Sep 17, 2023	Automatic Speech RecognitionDenoising	—Unverified
Controlling the Perceived Sound Quality for Dialogue Enhancement with Deep Learning	Jul 22, 2021	Speech Enhancement	—Unverified
Convoifilter: A case study of doing cocktail party speech recognition	Aug 22, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Convolutional Neural Network-based Speech Enhancement for Cochlear Implant Recipients	Jul 3, 2019	Speech Enhancement	—Unverified
Convolutional-Recurrent Neural Networks for Speech Enhancement	May 2, 2018	Speech Enhancement	—Unverified
ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion	Nov 5, 2018	Speech EnhancementVoice Conversion	—Unverified
Cooperative Dual Attention for Audio-Visual Speech Enhancement with Facial Cues	Nov 24, 2023	Speech Enhancement	—Unverified
Correlating Subword Articulation with Lip Shapes for Embedding Aware Audio-Visual Speech Enhancement	Sep 21, 2020	Speech Enhancement	—Unverified
Cross-attention conformer for context modeling in speech enhancement for ASR	Oct 30, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Cross-Attention is all you need: Real-Time Streaming Transformers for Personalised Speech Enhancement	Nov 8, 2022	AllSpeech Enhancement	—Unverified
Cross-domain Single-channel Speech Enhancement Model with Bi-projection Fusion Module for Noise-robust ASR	Aug 26, 2021	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
ctPuLSE: Close-Talk, and Pseudo-Label Based Far-Field, Speech Enhancement	Jul 28, 2024	Pseudo LabelSpeech Enhancement	—Unverified
Cycle-Consistent Speech Enhancement	Sep 6, 2018	Multi-Task LearningSpeech Enhancement	—Unverified

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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