Would you please share the demo for denoising_model training?

[youngsuenXMLY]

First, what brilliant work you have done!
I found your denoising demo without model training application. Would you please share a m-file for denoising model training. Your reply will be highly appreciated! Thank you.

[posenhuang]

I'll work on it recently :) It's a bit messy now. I'll update the thread once it is done.

[youngsuenXMLY]

Hi ,posenhuang
I mixed 2hours music and speech data at SNR=0 for training, and get satisfactory result. But there is still some problem in internal memory usage. I used a PC with 64GB internal memory, after formulate_data function in formulate_data .m, the internal memory is full, even worse the internal memory swap data with hard disk. I think the main reason is that in formulate_data function, the background music data(variable 'train2') is shift-repeated floor(lenghth(train2)/shift_size ) times, so the
feature data correspondingly increased.
Is there any solution to reduce internal memory usage?

[posenhuang]

You can try to adjust the shift size to reduce the memory. Also are you using drnn_mini? It is a mini-batch lbfgs. It should use less memory. FYI: I just pushed the training code here (merged to master): #18