Code Base (cIRM, Quantized)

cIRM = Complex Ideal Ratio Mask Quantized = Quantization Spec

Data

All the necessary data are in \data\knayem

Backup

Backup are in carbonate.uits.iu.edu. Full path is knayem@carbonate.uits.iu.edu:/N/u/knayem/Carbonate/Eagles_Backup/Data

File transfer

To transfer a file (file.txt) to another server. You should be logged in to the console of sending server (from-server).

scp file.txt remote_username@10.10.0.2:/remote/directory/newfilename.txt

To transfer folder (IEEE_DataFiles) from a server (e.g. eagles) to another server (e.g. carbonate)

scp IEEE_DataFiles knayem@carbonate.uits.iu.edu:/N/u/knayem/Carbonate/Eagles_Backup/Data

GPU check

nvidia-smi

Eagles

ssh -Y knayem@eagles.soic.indiana.edu

bash
cd EaglesBigred2/cIRM

For Matlab

matlab

scriptTrainDNN_cIRM_denoise_08('SSN')         
# SERVER = 'Eagles'; % 'BigRed2'
# VERSION = '_e10v1';

scriptTestDNN_cIRM_denoise_02()
# VERSION = '_e10v1';
# SERVER = 'Eagles'; % 'BigRed2'
# CODE = 'Matlab'; % 'Python'

calculatePESQ_02( VERSION )
SERVER = 'Eagles'; % 'BigRed2'
CODE = 'Matlab'; % 'Python'

For Python

matlab

scriptTrainDNN_cIRM_denoise_08('SSN')         
# SERVER = 'Eagles'; % 'BigRed2'
# VERSION = '_e10v1';

python DNN_01_8_v2.py

cd dnn_models/
cIRM_Net_Change(VERSION)

scriptTestDNN_cIRM_denoise_02()
# VERSION = '_e10v1';
# SERVER = 'Eagles'; % 'BigRed2'
# CODE = 'Python'; % 'Matlab'

calculatePESQ_02( VERSION )
SERVER = 'Eagles'; % 'BigRed2'
CODE = 'Python'; % 'Matlab'

Jupyter Notebook

ssh -Y -L localhost:8896:localhost:8888 knayem@eagles.soic.indiana.edu

jupyter notebook

Copy Server to Server To copy from BigRed2 to Eagles, from BigRed2,

scp -r <BigRed2_files>/ knayem@eagles.soic.indiana.edu:<Eagle_folder>/

Example:

scp -r denoising_mix_wavs_SSN_15000noisespercs/ knayem@eagles.soic.indiana.edu:/data/knayem/

Generate Noisy Audio

Go to /home/knayem/EaglesBigRed2/cIRM/GENERAL/ folder. Run createNoisySpeech_v2_1().

/home/knayem/EaglesBigRed2/cIRM/
      |---> GENERAL

Function createNoisySpeech_v2_1() prototype,

createNoisySpeech_v2_1(NOISE,TASK,SNR)

::parameter:: 
      NOISE : <str> case-insensitive; one of these 4 noises types 'SSN', 'CAFE', 'BABBLE', 'FACTORY'.
      TASK  : <str> case-insensitive; one of these 3 tasks types 'TRAIN', 'DEV', 'TEST'.
      SNR   : <int>; snr levels depends on task type. Train (-3,0,3), Dev (-3,0,3) and Test (-6,-3,0,3,-6).
      
::return::
      <none>
      Saved file name pattern 
      <filename1>_16k_<filename2>_<SNR>dB_<NOISE>_noisyspeech.wav
      S_72_09_16k_0_-3dB_FACTORY_noisyspeech.wav
      <filename1>=actual file name, <filename2>=serial of file name

By default, 10 audio (different cuts by adding various parts of a noise type) generated of an audio.

Note: Check the Clean_Wav_Save_Path and Noisy_Wav_Save_Path carefully. (Line 45-59)

BigRed 2

bigred2.uits.iu.edu

Directory

Home Directory

/gpfs/home/k/n/knayem/BigRed2

(home directory on BigRed2 that has a maximum storage area of 100GB.)

Code Directory

/gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Code/cIRM/cIRM

Data Directory

/gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Data

Matlab Commands to run cIRM codes

change files' path of scriptTestDNN_cIRM_denoise_02() and calculatePESQ_02() accordingly (matlab/python)

qsub -I -l walltime=10:00:00 -l nodes=1:ppn=4 -l gres=ccm -q gpu
module add ccm
ccmlogin
cd /gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Code/cIRM/cIRM
module add matlab/2016a
matlab

>> scriptTrainDNN_cIRM_denoise_02('SSN')

>> scriptTestDNN_cIRM_denoise_02()

>> cd PESQ
>> calculatePESQ_02()

Python Commands to run cIRM codes

change files' path of scriptTestDNN_cIRM_denoise_02() and calculatePESQ_02() accordingly (matlab/python)

qsub -I -l walltime=10:00:00 -l nodes=1:ppn=4 -l gres=ccm -q gpu
module add ccm
ccmlogin
cd /gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Code/cIRM/cIRM
module add tensorflow
module add anaconda2

python DNN_01.py

module add matlab/2016a
matlab

>> cd dnn_models
>> cIRM_Net_Change()

>> cd ..
>> scriptTestDNN_cIRM_denoise_02()

>> cd PESQ
>> calculatePESQ_02()

File Annotation

Clean Speech (SSN Noise), for Train+Development+Test

/gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Data/denoising_clean_wavs_SSN_10noisespercs
      |---> training_16k
            |---> S_01_01_16k.wav
            |
            |---> ... (total 500 files)
      |---> development_16k
            |---> S_51_01_16k.wav
            |
            |---> ... (total 110 files)
      |---> testing_16k
            |---> S_62_02_16k.wav
            |
            |---> ... (total 109 files)

Mix/Noisy Speech (SSN Noise), for Train+Development+Test

/gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Data/denoising_mix_wavs_SSN_10noisespercs
      |---> training_16k
            |---> S_01_01_16k_-3dB_noisyspeech.wav
            |---> S_01_01_16k_0dB_noisyspeech.wav
            |---> S_01_01_16k_3dB_noisyspeech.wav
            |
            |---> ... (total 500x3=1500 files, [-3dB,0dB,3dB] noise level)
      |---> development_16k
            |---> S_51_01_16k_-3dB_noisyspeech.wav
            |---> S_51_01_16k_0dB_noisyspeech.wav
            |---> S_51_01_16k_3dB_noisyspeech.wav
            |
            |---> ... (total 110x3=330 files, [-3dB,0dB,3dB] noise level)
      |---> testing_matched
            |---> S_62_02_16k_-3dB_noisyspeech.wav
            |---> S_62_02_16k_-6dB_noisyspeech.wav
            |---> S_62_02_16k_0dB_noisyspeech.wav
            |---> S_62_02_16k_3dB_noisyspeech.wav
            |---> S_62_02_16k_6dB_noisyspeech.wav
            |
            |---> ... (total 109x3= 545 files, [-6dB,-3dB,0dB,3dB,6dB] noise level)

Enhanced/Generated Speech (SSN Noise), from Testing

/gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Data/denoise_complex_domain_wavs
      |---> S_62_02_16k_-3dB_noisyspeech_crmenh.wav
      |---> S_62_02_16k_-6dB_noisyspeech_crmenh.wav
      |---> S_62_02_16k_0dB_noisyspeech_crmenh.wav
      |---> S_62_02_16k_3dB_noisyspeech_crmenh.wav
      |---> S_62_02_16k_6dB_noisyspeech_crmenh.wav
      |
      |---> ... (total 109x5= 545 files, [-6dB,-3dB,0dB,3dB,6dB] noise level)

Model files

/gpfs/home/k/n/knayem/BigRed2/Eagles_Backup/Code/cIRM/cIRM/dnn_models
      |---> dnncirm.noiseSSN.mat (Trained matlab Model)
            (MATLAB: scriptTrainDNN_cIRM_denoise('SSN')-> write )
      |---> dnncirm.noiseSSN_02.mat 
      |
      |---> DNN_datas.mat 
            (MATLAB: scriptTrainDNN_cIRM_denoise_mat('SSN')-> write)
            (PYTHON: DNN_01.py -> read)
            (MATLAB: cIRM_Net_Change()-> read)
      |---> DNN_params.mat
            (MATLAB: scriptTrainDNN_cIRM_denoise_mat('SSN')-> write)
            (PYTHON: DNN_01.py -> read)
            (MATLAB: cIRM_Net_Change()-> read)
      |
      |---> DNN_net.mat (Trained python Model [intermediate])
            (PYTHON: DNN_01.py -> write)
            (MATLAB: cIRM_Net_Change()-> read)
      |---> DNN_net_02.mat
      |
      |---> DNN_CIRM_net.mat (Trained python Model [final])
            (MATLAB: cIRM_Net_Change()-> write)
            (MATLAB: scriptTestDNN_cIRM_denoise()-> read)
      |---> DNN_CIRM_net_02.mat
      

scratch directory

/N/dc2/scratch/knayem (scratch space is automatically deleted after 60 days so make sure to move files you care about to your home directory.)

cd /N/dc2/scratch/knayem

Jupyter at BigRed2

Check at your pc if tcp:8895 is free or not. If not free (e.g. process <PID1> is running), then kill it.

lsof -i tcp:8895
kill -9 <PID1>
ssh -N -f -L localhost:8895:localhost:8895 knayem@bigred2.uits.iu.edu
ssh knayem@bigred2.uits.iu.edu

Run at the server,

lsof -i tcp:8895
kill -9 <PID2>
jupyter notebook --no-browser --port=8895

Module Commands

http://modules.sourceforge.net/man/module.html

Tip: GitHub README Basic writing and formatting syntax, https://help.github.com/articles/basic-writing-and-formatting-syntax/