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An Attention-based Neural Network Approach for Single Channel Speech Enhancement
speech enhancement\speech seperation\sound source localization
demo
A neural network consist of cnn and lstm for speech enhancement
全卷积网络进行语音降噪
Two-talker Speech Separation with LSTM/BLSTM by Permutation Invariant Training method.
Some MFC programs and Some demo
Experimental code to read/write NumPy .NPY files in MATLAB
An implementation of the ICASSP paper 'A fully convolutional neural network for complex spectrogram processing in speech enhancement'
deep learning based speech enhancement using keras or pytorch, make it easy to use
Signal Processing Tools for MATLAB
Deep learning for audio denoising
Speech-to-Text-WaveNet : End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow
Implementation of a fully convolutional neural network for speech enhancement
speech enhancement using DNN: [1] Xu, Y., Du, J., Dai, L.R. and Lee, C.H., 2015. A regression approach to speech enhancement based on deep neural networks. IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 23(1), pp.7-19. https://github.com/yongxuUSTC/sednn/tree/master/mixture2clean_dnn CRN: Park S R , Lee J . A Fully Convolutional Neural Network for Speech Enhancement[J]. 2016. DSN(still coding): Nie S , Zhang H , Zhang X L , et al. DEEP STACKING NETWORKS WITH TIME SERIES FOR SPEECH SEPARATION[J]. 2014.
Keras WaveNet implementation
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