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 901–925 of 982 papers

Title	Date	Tasks	Status	Hype
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking	Oct 11, 2018	Speaker RecognitionSpeaker Separation	CodeCode Available	2
Phasebook and Friends: Leveraging Discrete Representations for Source Separation	Oct 2, 2018	Speaker SeparationSpeech Enhancement	—Unverified	0
On Four Metaheuristic Applications to Speech Enhancement---Implementing Optimization Algorithms with MATLAB R2018a	Oct 1, 2018	Speech Enhancement	—Unverified	0
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech Separation	Sep 20, 2018	Multi-task Audio Source SeperationMusic Source Separation	CodeCode Available	3
New insights on the optimality of parameterized wiener filters for speech enhancement applications	Sep 19, 2018	Speech Enhancement	—Unverified	0
Cycle-Consistent Speech Enhancement	Sep 6, 2018	Multi-Task LearningSpeech Enhancement	—Unverified	0
Adversarial Feature-Mapping for Speech Enhancement	Sep 6, 2018	Speech Enhancement	—Unverified	0
Whispered-to-voiced Alaryngeal Speech Conversion with Generative Adversarial Networks	Aug 31, 2018	Speech EnhancementSpeech Recognition	CodeCode Available	0
Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments	Aug 28, 2018	Lip ReadingSpeech Enhancement	—Unverified	0
A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)	Aug 17, 2018	Quantizationregression	—Unverified	0
Quality-Net: An End-to-End Non-intrusive Speech Quality Assessment Model based on BLSTM	Aug 16, 2018	Speech Enhancement	—Unverified	0
Lip-Reading Driven Deep Learning Approach for Speech Enhancement	Jul 31, 2018	Acoustic ModellingDeep Learning	—Unverified	0
A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement	Jul 20, 2018	Speech Enhancement	—Unverified	0
Relative Transfer Function Estimation Exploiting Spatially Separated Microphones in a Diffuse Noise Field	Jul 12, 2018	Speech Enhancement	—Unverified	0
Speech Denoising Convolutional Neural Network trained with Deep Feature Losses.	Jun 27, 2018	Audio TaggingDenoising	CodeCode Available	0
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition	Jun 13, 2018	Data AugmentationDistant Speech Recognition	—Unverified	0
Convolutional-Recurrent Neural Networks for Speech Enhancement	May 2, 2018	Speech Enhancement	—Unverified	0
Boosting Noise Robustness of Acoustic Model via Deep Adversarial Training	May 2, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Recent Progresses in Deep Learning based Acoustic Models (Updated)	Apr 25, 2018	Deep LearningGeneral Classification	—Unverified	0
The Conversation: Deep Audio-Visual Speech Enhancement	Apr 11, 2018	Speech Enhancement	—Unverified	0
The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines	Mar 28, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Student-Teacher Learning for BLSTM Mask-based Speech Enhancement	Mar 27, 2018	Speech Enhancementspeech-recognition	—Unverified	0
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline	Mar 27, 2018	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified	0
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition	Mar 27, 2018	Robust Speech RecognitionSpeech Dereverberation	CodeCode Available	0
Spectral feature mapping with mimic loss for robust speech recognition	Mar 26, 2018	Robust Speech RecognitionSpeech Enhancement	—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