文件名称:DNN_toolbox

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语音分离用的深度神经网络工具箱,matlab,非常全

-This folder contains Matlab programs for a toolbox for supervised speech separation using deep neural networks (DNNs).
(系统自动生成,下载前可以参看下载内容)

下载文件列表





DNN_toolbox

...........\config

...........\......\list.txt

...........\......\list120.txt

...........\......\list120_short.txt

...........\......\list600.txt

...........\......\list600_short.txt

...........\DATA

...........\dnn

...........\...\main

...........\...\....\checkPerformanceOnData_no_print.m

...........\...\....\checkPerformanceOnData_no_print_wiener.m

...........\...\....\checkPerformanceOnData_save_IBM.m

...........\...\....\checkPerformanceOnData_save_wiener.m

...........\...\....\computeNetGradientNoRolling.m

...........\...\....\dnn_train.m

...........\...\....\forwardPass.m

...........\...\....\forwardPass_diff_drop_ratio.m

...........\...\....\funcDeepNetTrainNoRolling.m

...........\...\....\getOutputFromNet.m

...........\...\....\getOutputFromNetSplit.m

...........\...\....\stoi.m

...........\...\mvn_store.m

...........\...\pretraining

...........\...\...........\pretrainRBMStack.m

...........\...\...........\trainRBM.m

...........\...\run_every.m

...........\...\utility

...........\...\.......\batchComputeMeanStd.m

...........\...\.......\compute_unit_activation.m

...........\...\.......\compute_unit_gradient.m

...........\...\.......\count_struct.m

...........\...\.......\deltas.m

...........\...\.......\format_print.m

...........\...\.......\gather_net.m

...........\...\.......\genBatchID.m

...........\...\.......\getHITFA.m

...........\...\.......\getMSE.m

...........\...\.......\getNetParamStr.m

...........\...\.......\initializeRandWSparse.m

...........\...\.......\initRandW.m

...........\...\.......\initRandWSparse.m

...........\...\.......\make_labels.m

...........\...\.......\make_window_buffer.m

...........\...\.......\meanVarArmaNormalize_Test.m

...........\...\.......\meanVarNormalize.m

...........\...\.......\meanVarNormalize_Test.m

...........\...\.......\mean_var_norm.m

...........\...\.......\mean_var_norm_testing.m

...........\...\.......\netRolling.m

...........\...\.......\netUnRolling.m

...........\...\.......\randInitNet.m

...........\...\.......\randinitWbSparse.m

...........\...\.......\relu.m

...........\...\.......\relu_grad.m

...........\...\.......\resyn

...........\...\.......\.....\cochleagram.m

...........\...\.......\.....\cochplot.m

...........\...\.......\.....\erb2hz.m

...........\...\.......\.....\f_af_bf_cf.mat

...........\...\.......\.....\gammatone.m

...........\...\.......\.....\hz2erb.m

...........\...\.......\.....\ibm.m

...........\...\.......\.....\loudness.m

...........\...\.......\.....\meddis.m

...........\...\.......\.....\synthesis.m

...........\...\.......\sigmoid.m

...........\...\.......\sigmoid_grad.m

...........\...\.......\softmax.m

...........\...\.......\unroll_struct.m

...........\...\.......\zeroInitNet.m

...........\gen_mixture

...........\...........\generate_test_mix.m

...........\...........\generate_train_mix.m

...........\...........\get_all_noise_test.m

...........\...........\get_all_noise_train.m

...........\get_feat

...........\........\features

...........\........\........\ams

...........\........\........\...\AMS_init_FFT.m

...........\........\........\...\create_crit_filter.m

...........\........\........\...\env_extraction_gmt_chan2.m

...........\........\........\...\extract_AMS_perChan.m

...........\........\........\...\get_amsfeature_chan_fast.m

...........\........\........\...\mel.m

...........\........\........\cochleagram

...........\........\........\...........\cochleagram.m

...........\........\........\...........\erb2hz.m

...........\........\........\...........\f_af_bf_cf.mat

...........\........\........\...........\gammatone.m

...........\........\........\...........\hz2erb.m

...........\........\........\...........\ibm.m

...........\........\........\...........\ideal.m

...........\........\........\...........\loudness.m

...........\........\........\...........\meddis.m

...........\........\........\...........\synthesis.m

...........\........\........\...........\wiener.m

...........\........\........\my_features_AmsRastaplpMfccGf.m

...........\........\........\rastamat

...........\........\........\..

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