comparison userProgramsASRforDummies/Exp_Tutorial_2.m @ 38:c2204b18f4a2 tip

End nov big change

+function Exp_Tutorial_2(isMasterNode)
+
+% This tutorial recycles a HMM
+
+%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Set up the basic experiment parameters
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+expName = 'Tutorial';
+dataFolderPrefix = 'recycle_featR';
+if isunix
+    expFolderPrefix = '/scratch/nrclark/exps/';
+else
+    expFolderPrefix = 'D:\Exps';
+end
+
+% expFolderPrefix = pwd;
+expFolder = fullfile(expFolderPrefix,expName);
+hmmFolder = fullfile(expFolder,'hmm');
+
+%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Sort out the training (LEARNING) condition
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+learnFolder = fullfile(expFolder,'featL');
+
+xL = cJob('L', learnFolder);
+
+xL.participant = 'Normal';
+xL.MAPparamChanges= {'DRNLParams.rateToAttenuationFactorProb=0;', 'OMEParams.rateToAttenuationFactorProb=0;' };
+
+xL.noiseLevToUse   =  -200;
+xL.speechLevToUse  =  60;
+
+xL.MAPopHSR = 1;
+xL.MAPopMSR = 0;
+xL.MAPopLSR = 0;
+
+
+xL.numCoeff = 14;
+xL.removeEnergyStatic = 0;
+
+%%%%% Group of params that will influence simulation run time %%%%%%%
+xL.numWavs = 12; %MAX=8440
+testWavs = 6; %MAX = 358
+nzLevel = [-200 40:10:70];
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+xL.noisePreDur = 1;
+xL.noisePostDur = 0.1;
+xL.truncateDur  = xL.noisePreDur-0.1; 
+xL.noiseName = 'pink_demo';
+
+
+% if isMasterNode && ~isdir(xL.opFolder)
+%     mkdir(xL.opFolder);
+%     xL = xL.assignFiles;
+%     xL.storeSelf;
+% end
+
+%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Sort out the testing (RECOGNITION) conditions
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+recConditions = numel(nzLevel);
+
+tmpIdx=0;
+for nn = 0*recConditions+1:1*recConditions    
+    tmpIdx=tmpIdx+1;
+    xR{nn} = xL; %simply copy the "Learn" object and change it a bit below
+    recFolder = fullfile(expFolder,[dataFolderPrefix num2str(nn)]);
+    xR{nn}.opFolder = recFolder;    
+    
+    %These are the interesting differences between training and testing
+    xR{nn}.numWavs = testWavs; %MAX = 358
+    xR{nn}.noiseLevToUse = nzLevel(tmpIdx); 
+    xR{nn}.MAPparamChanges= {'DRNLParams.a=400;'};
+
+    
+    %Now just to wrap it up ready for processing
+    if isMasterNode && ~isdir(xR{nn}.opFolder)
+        mkdir(xR{nn}.opFolder);
+        xR{nn} = xR{nn}.assignWavPaths('R');
+        xR{nn} = xR{nn}.assignFiles;
+        xR{nn}.storeSelf;
+    end
+end
+
+tmpIdx=0;
+for nn = 1*recConditions+1:2*recConditions    
+    tmpIdx=tmpIdx+1;
+    xR{nn} = xL; %simply copy the "Learn" object and change it a bit below
+    recFolder = fullfile(expFolder,[dataFolderPrefix num2str(nn)]);
+    xR{nn}.opFolder = recFolder;    
+    
+    %These are the interesting differences between training and testing
+    xR{nn}.numWavs = testWavs; %MAX = 358
+    xR{nn}.noiseLevToUse = nzLevel(tmpIdx); 
+    xR{nn}.MAPparamChanges= {'DRNLParams.a=400;'};
+    
+    xR{nn}.mainGain = [27.2013;   26.0797;   26.0939;   26.7997;   26.0520];  
+    xR{nn}.TCdBO    = [37;   37;   37;   37;   37];      %Compression thresholds (in dB OUTPUT from 2nd filt)
+    xR{nn}.TMdBO    = [20;   20;   20;   20;   20];      %MOC thresholds (in dB OUTPUT from 2nd filt)
+    xR{nn}.ARthresholddB = 85;       % dB SPL (input signal level) =>200 to disable
+    xR{nn}.MOCtau = 1;
+    xR{nn}.useAid = 1;
+    
+    %Now just to wrap it up ready for processing
+    if isMasterNode && ~isdir(xR{nn}.opFolder)
+        mkdir(xR{nn}.opFolder);
+        xR{nn} = xR{nn}.assignWavPaths('R');
+        xR{nn} = xR{nn}.assignFiles;
+        xR{nn}.storeSelf;
+    end
+end
+
+
+
+%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% ** Generate features **
+% This is the time consuming, processing intensive portion of the program.
+% Nodes that are not the master node are only interested in the opFolder
+% member of the jobjects.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% worker(xL.opFolder);
+maxConds = nn;
+if ~isMasterNode %dont bother wasting master node effort on generating testing features (for now)
+    for nn = 1:maxConds
+        worker(xR{nn}.opFolder);
+    end
+end
+
+%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Train and test the recogniser - a job for the master node only
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+if isMasterNode    
+%     while(~all(xL.todoStatus==2))        
+%         disp('Waiting on straggler nodes to complete their jobs before HMM is trained . . .')
+%         pause(30); %Wait for 30 seconds before looking again
+%         xL.lockJobList;
+%         xL = xL.loadSelf; %Reload incase changed
+%         xL.unlockJobList;
+%     end
+    y = cHMM(hmmFolder);    
+    y.numCoeff = 14*3;
+%     y.createSCP(xL.opFolder)
+%     y.createMLF(xL.opFolder)
+%     y.train(xL.opFolder) %This node can be busy training, even if other jobs are being processed for testing
+    
+    % ALLOW MASTER NODE TO MUCK IN WITH GENERATING TESTING FEATURES ONCE
+    % HMM HAS BEEN TRAINED
+    for nn = 1:maxConds
+        worker(xR{nn}.opFolder);
+    end    
+    
+    xR{end}.lockJobList;
+    xR{end} = xR{end}.loadSelf; %Reload changes
+    xR{end}.unlockJobList;
+    while(~all(xR{end}.todoStatus==2))        
+        disp('Waiting on straggler nodes to complete their jobs before HMM is tested . . .')
+        pause(30); %Wait for 30 seconds before looking again
+        xR{end}.lockJobList;
+        xR{end} = xR{end}.loadSelf; %Reload incase changed
+        xR{end}.unlockJobList;
+    end
+      
+    for nn = 1:maxConds
+        y.createSCP(xR{nn}.opFolder);
+        y.test(xR{nn}.opFolder);
+    end
+    
+    %Show all of the scores in the command window at the end
+    for nn = 1:maxConds
+        y.score(xR{nn}.opFolder);
+    end
+end