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 901950 of 982 papers

TitleStatusHype
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram MaskingCode2
Phasebook and Friends: Leveraging Discrete Representations for Source Separation0
On Four Metaheuristic Applications to Speech Enhancement---Implementing Optimization Algorithms with MATLAB R2018a0
Conv-TasNet: Surpassing Ideal Time-Frequency Magnitude Masking for Speech SeparationCode3
New insights on the optimality of parameterized wiener filters for speech enhancement applications0
Cycle-Consistent Speech Enhancement0
Adversarial Feature-Mapping for Speech Enhancement0
Whispered-to-voiced Alaryngeal Speech Conversion with Generative Adversarial NetworksCode0
Contextual Audio-Visual Switching For Speech Enhancement in Real-World Environments0
A study on speech enhancement using exponent-only floating point quantized neural network (EOFP-QNN)0
Quality-Net: An End-to-End Non-intrusive Speech Quality Assessment Model based on BLSTM0
Lip-Reading Driven Deep Learning Approach for Speech Enhancement0
A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement0
Relative Transfer Function Estimation Exploiting Spatially Separated Microphones in a Diffuse Noise Field0
Speech Denoising Convolutional Neural Network trained with Deep Feature Losses.Code0
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition0
Convolutional-Recurrent Neural Networks for Speech Enhancement0
Boosting Noise Robustness of Acoustic Model via Deep Adversarial Training0
Recent Progresses in Deep Learning based Acoustic Models (Updated)0
The Conversation: Deep Audio-Visual Speech Enhancement0
The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines0
Student-Teacher Learning for BLSTM Mask-based Speech Enhancement0
Building state-of-the-art distant speech recognition using the CHiME-4 challenge with a setup of speech enhancement baseline0
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech RecognitionCode0
Spectral feature mapping with mimic loss for robust speech recognition0
Can we steal your vocal identity from the Internet?: Initial investigation of cloning Obama's voice using GAN, WaveNet and low-quality found data0
Speech Enhancement in Adverse Environments Based on Non-stationary Noise-driven Spectral Subtraction and SNR-dependent Phase Compensation0
Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy0
Enhancement of Noisy Speech Exploiting an Exponential Model Based Threshold and a Custom Thresholding Function in Perceptual Wavelet Packet Domain0
Deep Learning Based Speech Beamforming0
Enhancement of Noisy Speech with Low Speech Distortion Based on Probabilistic Geometric Spectral Subtraction0
Language and Noise Transfer in Speech Enhancement Generative Adversarial NetworkCode0
Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification0
Reinforcement Learning To Adapt Speech Enhancement to Instantaneous Input Signal Quality0
Visual Speech Enhancement0
Exploring Speech Enhancement with Generative Adversarial Networks for Robust Speech Recognition0
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
Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization0
Contaminated speech training methods for robust DNN-HMM distant speech recognitionCode0
Nonnegative HMM for Babble Noise Derived from Speech HMM: Application to Speech Enhancement0
Supervised and Unsupervised Speech Enhancement Using Nonnegative Matrix FactorizationCode0
End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks0
Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks0
Supervised Speech Separation Based on Deep Learning: An Overview0
Perceptual audio loss function for deep learning0
Proximal Policy Optimization AlgorithmsCode2
Face Recognition with Machine Learning in OpenCV_ Fusion of the results with the Localization Data of an Acoustic Camera for Speaker Identification0
Hidden-Markov-Model Based Speech Enhancement0
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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