yong xu @ seattle

You are right. cudaMemcpy(dev[0].out,cur_layer_x,n_frames*cur_layer_units*sizeof(float),cudaMemcpyDeviceToDevice); I think i uploaded the code for ideal binary mask prediction. I commented the sigmoid code, but forgot to change "cur_layer_y" to "cur_layer_x". I have updated...

please update "cv_bunch_single" func also

If you want to check your code, you can map from clean to clean, if it still does not work. That means your code has some problem. You should do...

Hi, you should first use HTK toolset (or the tool in my decoding tool) to extract log-power spectra (not wav) feature, and then use quicknet tool to merge into big...

Hi i update the detailed steps to get pfile and add some toolset: https://github.com/yongxuUSTC/DNN-for-speech-enhancement/blob/master/how_to_get_pfile.txt # detailed steps for get pfile # step1: used the tool "Wav2LogSpec.exe" to extract all ".lsp"...

You should first understand "frame" concept in speech processing. your method to get ".len" file is wrong. ".len" stores the frame number info for each fea file. you can get...

wav2logspec.exe can extract the feature, but it is in "le" format, you should convert it into "be" format. And then use feacat to combine fea and len. Note that ".len"...

Do you give the full path of each feature file? Sorry, i think it is Lunix basic problems, try to use google to search the answers. Or you can dig...

Yes, QNNORM is used to prepare .fea_norm For the target feature, it also should be normalized which is similar to input feature. I thought it maybe because i used it...

Please use matlab to run "step1_DNNenh_for16kHz.m", it should work very well. Do not use "step1_DNNenh_for16kHz.exe"