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资源汇总

资源汇总

关于语音增强、去混响、分离及阵列相关资源的汇总，欢迎PR，感谢 star。

Contents

Speech_Enhancement

Magnitude spectrogram

spectral masking

spectral mapping

  • 2014, An Experimental Study on Speech Enhancement Based on Deep Neural Networks, Xu. [Paper]

  • 2014, A Regression Approach to Speech Enhancement Based on Deep Neural Networks, Xu. [Paper] [sednn] [DNN-SE-Xu] [DNN-SE-Li]

  • Other DNN magnitude spectrum mapping-based SE repositories: [SE toolkit] [TensorFlow-SE] [UNetSE]

  • 2015, Speech enhancement with LSTM recurrent neural networks and its application to noise-robust ASR, Weninger. [Paper]

  • 2016, A Fully Convolutional Neural Network for Speech Enhancement, Park. [Paper] [CNN4SE]

  • 2017, Long short-term memory for speaker generalizationin supervised speech separation, Chen. [Paper]

  • 2018, A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement, Tan. [Paper] [CRN-Tan]

  • 2018, Convolutional-Recurrent Neural Networks for Speech Enhancement, Zhao. [Paper] [CRN-Hao]

Complex domain

  • 2017, Complex spectrogram enhancement by convolutional neural network with multi-metrics learning, Fu. [Paper]
  • 2017, Time-Frequency Masking in the Complex Domain for Speech Dereverberation and Denoising, Williamson. [Paper]
  • 2019, PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Network, Yin. [Paper] [PHASEN]
  • 2019, Phase-aware Speech Enhancement with Deep Complex U-Net, Choi. [Paper] [DC-UNet]
  • 2020, Learning Complex Spectral Mapping With GatedConvolutional Recurrent Networks forMonaural Speech Enhancement, Tan. [Paper] [GCRN]
  • 2020, DCCRN: Deep Complex Convolution Recurrent Network for Phase-AwareSpeech Enhancement, Hu. [Paper] [DCCRN]
  • 2020, T-GSA: Transformer with Gaussian-Weighted Self-Attention for Speech Enhancement, Kim. [Paper]
  • 2020, Phase-aware Single-stage Speech Denoising and Dereverberation with U-Net, Choi. [Paper]

Time domain

  • 2018, Improved Speech Enhancement with the Wave-U-Net, Macartney. [Paper] [WaveUNet]
  • 2019, A New Framework for CNN-Based Speech Enhancement in the Time Domain, Pandey. [Paper]
  • 2019, TCNN: Temporal Convolutional Neural Network for Real-time Speech Enhancement in the Time Domain, Pandey. [Paper]
  • 2020, Real Time Speech Enhancement in the Waveform Domain, Defossez. [Paper] [facebookDenoiser]
  • 2020, Monaural speech enhancement through deep wave-U-net, Guimarães. [Paper] [SEWUNet]
  • 2020, Speech Enhancement Using Dilated Wave-U-Net: an Experimental Analysis, Ali. [Paper]
  • 2020, Densely Connected Neural Network with Dilated Convolutions for Real-Time Speech Enhancement in the Time Domain, Pandey. [Paper] [DDAEC]
  • 2021, Dense CNN With Self-Attention for Time-Domain Speech Enhancement, Pandey. [Paper]
  • 2021, Dual-path Self-Attention RNN for Real-Time Speech Enhancement, Pandey. [Paper]

GAN

  • 2017, SEGAN: Speech Enhancement Generative Adversarial Network, Pascual. [Paper] [SEGAN]
  • 2019, SERGAN: Speech enhancement using relativistic generative adversarial networks with gradient penalty, Deepak Baby. [Paper] [SERGAN]
  • 2019, MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement, Fu. [Paper] [MetricGAN]
  • 2019, MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement, Fu. [Paper] [MetricGAN+]
  • 2020, HiFi-GAN: High-Fidelity Denoising and Dereverberation Based on Speech Deep Features in Adversarial Networks, Su. [Paper] [HifiGAN]

Hybrid SE

  • 2019, Deep Xi as a Front-End for Robust Automatic Speech Recognition, Nicolson. [Paper] [DeepXi]
  • 2019, Using Generalized Gaussian Distributions to Improve Regression Error Modeling for Deep-Learning-Based Speech Enhancement, Li. [Paper] [SE-MLC]
  • 2020, Deep Residual-Dense Lattice Network for Speech Enhancement, Nikzad. [Paper] [RDL-SE]
  • 2020, DeepMMSE: A Deep Learning Approach to MMSE-based Noise Power Spectral Density Estimation, Zhang. [Paper]
  • 2020, Speech Enhancement Using a DNN-Augmented Colored-Noise Kalman Filter, Yu. [Paper] [DNN-Kalman]

Multi-stage

  • 2020, A Recursive Network with Dynamic Attention for Monaural Speech Enhancement, Li. [Paper] [DARCN]
  • 2020, Masking and Inpainting: A Two-Stage Speech Enhancement Approach for Low SNR and Non-Stationary Noise, Hao. [Paper]
  • 2020, A Joint Framework of Denoising Autoencoder and Generative Vocoder for Monaural Speech Enhancement, Du. [Paper]
  • 2020, Dual-Signal Transformation LSTM Network for Real-Time Noise Suppression, Westhausen. [Paper] [DTLN]
  • 2020, Listening to Sounds of Silence for Speech Denoising, Xu. [Paper] [LSS]
  • 2021, ICASSP 2021 Deep Noise Suppression Challenge: Decoupling Magnitude and Phase Optimization with a Two-Stage Deep Network, Li. [Paper]
  • 2022, Glance and Gaze: A Collaborative Learning Framework for Single-channel Speech Enhancement, Li [Paper]
  • 2022, HGCN : harmonic gated compensation network for speech enhancement, Wang. [Paper]

Data collection

Loss

Challenge

Other repositories

  • Collection of papers, datasets and tools on the topic of Speech Dereverberation and Speech Enhancement [Link]
  • nanahou's awesome speech enhancement [Link]

Dereverberation

Traditional method

Hybrid method

NN-based Derev

Speech Separation (single channel)

  • Tutorial speech separation, like awesome series [Link]

NN-based separation

  • 2015, Deep-Clustering:Discriminative embeddings for segmentation and separation, Hershey and Chen.[Paper] [Code] [Code] [Code]
  • 2016, DANet:Deep Attractor Network (DANet) for single-channel speech separation, Chen.[Paper] [Code]
  • 2017, Multitalker speech separation with utterance-level permutation invariant training of deep recurrent, Yu.[Paper] [Code]
  • 2018, LSTM_PIT_Speech_Separation [Code]
  • 2018, Tasnet: time-domain audio separation network for real-time, single-channel speech separation, Luo.[Paper][Code]
  • 2019, Conv-TasNet: Surpassing Ideal Time-Frequency Masking for Speech Separation, Luo.(Paper)[Code]
  • 2019, Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation, Luo.[Paper][Code1] [Code2]
  • 2019, TAC end-to-end microphone permutation and number invariant multi-channel speech separation, Luo.[Paper] [Code]
  • 2020, Continuous Speech Separation with Conformer, Chen.[Paper] [Code]
  • 2020, Dual-Path Transformer Network: Direct Context-Aware Modeling for End-to-End Monaural Speech Separation, Chen.[Paper] [Code]
  • 2020, Wavesplit: End-to-End Speech Separation by Speaker Clustering, Zeghidour.[Paper]
  • 2021, Attention is All You Need in Speech Separation, Subakan.[Paper] [Code]
  • 2021, Ultra Fast Speech Separation Model with Teacher Student Learning, Chen.[Paper]
  • sound separation(Google) [Code]
  • sound separation: Deep learning based speech source separation using Pytorch [Code]
  • music-source-separation [Code]
  • Singing-Voice-Separation [Code]
  • Comparison-of-Blind-Source-Separation-techniques[Code]

BSS/ICA method

  • FastICA[Code]
  • A localisation- and precedence-based binaural separation algorithm[Download]
  • Convolutive Transfer Function Invariant SDR [Code]

Array Signal Processing

  • MASP:Microphone Array Speech Processing [Code]
  • BeamformingSpeechEnhancer [Code]
  • TSENet [Code]
  • steernet [Code]
  • DNN_Localization_And_Separation [Code]
  • nn-gev:Neural network supported GEV beamformer CHiME3 [Code]
  • chime4-nn-mask:Implementation of NN based mask estimator in pytorch（reuse some programming from nn-gev）[Code]
  • beamformit_matlab:A MATLAB implementation of CHiME4 baseline Beamformit [Code]
  • pb_chime5:Speech enhancement system for the CHiME-5 dinner party scenario [Code]
  • beamformit:麦克风阵列算法 [Code]
  • Beamforming-for-speech-enhancement [Code]
  • deepBeam [Code]
  • NN_MASK [Code]
  • Cone-of-Silence [Code]
  • binauralLocalization [Code]
  • robotaudition_examples:Some Robot Audition simplified examples (sound source localization and separation), coded in Octave/Matlab [Code]
  • WSCM-MUSIC [Code]
  • doa-tools [Code]
  • Regression and Classification for Direction-of-Arrival Estimation with Convolutional Recurrent Neural Networks [Code] [PDF]
  • messl:Model-based EM Source Separation and Localization [Code]
  • messlJsalt15:MESSL wrappers etc for JSALT 2015, including CHiME3 [Code]
  • fast_sound_source_localization_using_TLSSC:Fast Sound Source Localization Using Two-Level Search Space Clustering[Code]
  • Binaural-Auditory-Localization-System [Code]
  • Binaural_Localization:ITD-based localization of sound sources in complex acoustic environments [Code]
  • Dual_Channel_Beamformer_and_Postfilter [Code]
  • 麦克风声源定位 [Code]
  • RTF-based-LCMV-GSC [Code]
  • DOA [Code]

Sound Event Detection

  • sed_eval - Evaluation toolbox for Sound Event Detection [Code]
  • Benchmark for sound event localization task of DCASE 2019 challenge [Code]
  • sed-crnn DCASE 2017 real-life sound event detection winning method. [Code]
  • seld-net [Code]

Tools

  • APS:A workspace for single/multi-channel speech recognition & enhancement & separation. [Code]
  • AKtools:the open software toolbox for signal acquisition, processing, and inspection in acoustics [SVN Code](username: aktools; password: ak)
  • espnet [Code]
  • asteroid:The PyTorch-based audio source separation toolkit for researchers[PDF][Code]
  • pytorch_complex [Code]
  • ONSSEN: An Open-source Speech Separation and Enhancement Library [Code]
  • separation_data_preparation[Code]
  • MatlabToolbox [Code]
  • athena-signal [[Code]](https://github.com/athena-team/athena-signal）
  • python_speech_features [Code]
  • speechFeatures:语音处理，声源定位中的一些基本特征 [Code]
  • sap-voicebox [Code]
  • Calculate-SNR-SDR [Code]
  • RIR-Generator [Code]
  • Python library for Room Impulse Response (RIR) simulation with GPU acceleration [Code]
  • ROOMSIM:binaural image source simulation [Code]
  • binaural-image-source-model [Code]
  • PESQ [Code]
  • SETK: Speech Enhancement Tools integrated with Kaldi [Code]
  • pb_chime5:Speech enhancement system for the CHiME-5 dinner party scenario [Code]

Resources

  • Speech Signal Processing Course(ZH) [Link]
  • Speech Algorithms(ZH) [Link]
  • Speech Resources[Link]
  • CCF语音对话与听觉专业组语音对话与听觉前沿研讨会(ZH) [Link]

posted on 2022-04-02 21:48  WenzheLiu  阅读(825)  评论(0)  编辑  收藏  举报

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