yongxuUSTC/DCASE2016_DNN_scene_classification

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Created over 8 years ago
Updated over 8 years ago

yongxuUSTC/DCASE2016_DNN_scene_classification

yongxuUSTC

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sednn

deep learning based speech enhancement using keras or pytorch, make it easy to use

DNN-for-speech-enhancement

DNN-for-speech-enhancement

DNN-Speech-enhancement-demo-tool

Universal Deep neural network based speech enhancement demo and tools, well pre-trained DNN model

aDAE_DNN_audio_tagging

mtmvdr

Demo for Neural Spatio-Temporal Beamformer for Target Speech Separation accepted to INTERSPEECH2020

grnnbf

Generalized RNN beamformer for speech separation

convolutional-autoencoder-for-raw-waveform-reconstruction

convolutional autoencoder for raw waveform reconstruction to replace the classic STFT, i called it as short-time AE transform (STAET)

cnn_rnn_spatial_audio_tagging

dcase2017_task4_cvssp

DCASE2016_DNN_audio_tagging

conv_speech-For-distant-ASR-project--YongXU

conv_speech-For-distant-ASR-project--YongXU

code_for_IS15_DNNmultiObjLearn_speech_enhancement

print_tfrecord2numpy_tensorflow

print out the value of tfrecord file of tensorflow. It can also save the values of tfrecord to numpy or write in python pickle file.