Dimitrios@0: function [] = try_eventdetection(inputFile,outputFile)
Dimitrios@0: % Perform event detection and produce collective results
Dimitrios@0: % for all different configurations
Dimitrios@0: 
Dimitrios@0: % Suggested name for outputFile: 'Outputs_(sid/bdm)/XX/scriptXX.txt'
Dimitrios@0: 
Dimitrios@0: % This script assumes that the system outputs are text files saved in a 
Dimitrios@0: % preexisting folder "Outputs_<annotator>" and their names are of the form:
Dimitrios@0: % 'Outputs_(bdm/sid)/XX/scriptXX<...>.txt
Dimitrios@0: % where <...> is: _Bases_X-XX_thres_XXXX_filt_X
Dimitrios@0: 
Dimitrios@0: % All possible runs:
Dimitrios@0: %{
Dimitrios@0:  try_eventdetection('Development_Set/stereo/script01.wav','Outputs_sid/01/script01.txt');
Dimitrios@0:  try_eventdetection('Development_Set/stereo/script02.wav','Outputs_sid/02/script02.txt');
Dimitrios@0:  try_eventdetection('Development_Set/stereo/script03.wav','Outputs_sid/03/script03.txt');
Dimitrios@0:  try_eventdetection('Development_Set/stereo/script01.wav','Outputs_bdm/01/script01.txt');
Dimitrios@0:  try_eventdetection('Development_Set/stereo/script02.wav','Outputs_bdm/02/script02.txt');
Dimitrios@0:  try_eventdetection('Development_Set/stereo/script03.wav','Outputs_bdm/03/script03.txt');
Dimitrios@0: %}
Dimitrios@0: 
Dimitrios@0: % If normalised use thresholds: [200:50:900] and let line 53 on
Dimitrios@0: % If unnormalised use thresholds: [0:0.1:2.4] and comment out line 53
Dimitrios@0: 
Dimitrios@0: %Choose Annotation
Dimitrios@0: Annotators = {'_bdm', '_sid'};
Dimitrios@0: if isequal(outputFile(8:11),Annotators{1})
Dimitrios@0: ANOT_FLAG = 1;
Dimitrios@0: elseif isequal(outputFile(8:11),Annotators{2})
Dimitrios@0: ANOT_FLAG = 2;
Dimitrios@0: else
Dimitrios@0:     error('Incorrect outputFile, please see description again.');
Dimitrios@0: end
Dimitrios@0: 
Dimitrios@0: 
Dimitrios@0: % Different Combinations
Dimitrios@0: AllnumBases = [ 5 8 10 12 15 20 20]; % Last number(20) corresponds to Dict20individual
Dimitrios@0: AllFiltering = [ 1 3 5 ];
Dimitrios@0: AllThres = [200:50:900];  
Dimitrios@0: 
Dimitrios@0: for i = 1 : length(AllnumBases)
Dimitrios@0:     % Initialize
Dimitrios@0:     if (i == length(AllnumBases))
Dimitrios@0:         loadfile = ['Dictionaries' Annotators{ANOT_FLAG} '/Dict20individual' '.mat'];
Dimitrios@0:     else
Dimitrios@0:         loadfile = ['Dictionaries' Annotators{ANOT_FLAG} '/Dict' num2str(AllnumBases(i)) '.mat'];
Dimitrios@0:     end
Dimitrios@0:     load(loadfile);
Dimitrios@0:     Classes = {'alert','clearthroat','cough','doorslam','drawer','keyboard','keyes',...
Dimitrios@0:         'knock','laughter','mouse','pageturn','pendrop','phone','printer',...
Dimitrios@0:         'speech','switch'};
Dimitrios@0:     
Dimitrios@0:     
Dimitrios@0:     % Read the audio for the Event, making sure no overflow occurs
Dimitrios@0:     [x,fs] = wavread(inputFile);
Dimitrios@0:     
Dimitrios@0:     
Dimitrios@0:     % Normalize wav files
Dimitrios@0:     xnow = sum(x,2)/2;
Dimitrios@0:     % If choosing not to normalize, the thershold parameter above has to be
Dimitrios@0:     % adjusted: i.e. [0:0.1:2.2];
Dimitrios@0:     xnow = xnow./std(xnow); 
Dimitrios@0:     
Dimitrios@0:     
Dimitrios@0:     % Calculate CQT
Dimitrios@0:     [intCQT] = computeCQT(xnow);
Dimitrios@0:     cqt_rep = intCQT(:,round(1:7.1128:size(intCQT,2)));
Dimitrios@0:     
Dimitrios@0:     
Dimitrios@0:     % Perform NMF
Dimitrios@0:     [W,H,errs,vout] = nmf_beta(cqt_rep,size(Dict,2),'beta',1,'W',Dict,'W0',Dict);
Dimitrios@0:     
Dimitrios@0:     
Dimitrios@0:     % Reshape H
Dimitrios@0:     Hnew = reshape(H,AllnumBases(i),16,size(H,2));
Dimitrios@0:     Hnew2 = squeeze(sum(Hnew,1));
Dimitrios@0:     
Dimitrios@0:     for j = 1 : length(AllThres)
Dimitrios@0:         for k = 1 : length(AllFiltering)
Dimitrios@0:             % Perform thresolding on Hnew2
Dimitrios@0:             thr = AllThres(j);
Dimitrios@0:             Hnew2 = medfilt1(Hnew2',AllFiltering(k))';
Dimitrios@0:             eventRoll = double(Hnew2 > thr);
Dimitrios@0:             
Dimitrios@0:             
Dimitrios@0:             % Create matrix of events (onset-offset-classNum)
Dimitrios@0:             auxEventRoll = diff([zeros(1,16); eventRoll'; zeros(1,16);],1); p=0;
Dimitrios@0:             nmat=[];
Dimitrios@0:             for m=1:16
Dimitrios@0:                 onsets = find(auxEventRoll(:,m)==1);
Dimitrios@0:                 offsets = find(auxEventRoll(:,m)==-1);
Dimitrios@0:                 for n=1:length(onsets)
Dimitrios@0:                     if((offsets(n)/100-0.01) - (onsets(n)/100) > 0.05) % not output really short events
Dimitrios@0:                         p=p+1;
Dimitrios@0:                         nmat(p,1) = onsets(n)/100;
Dimitrios@0:                         nmat(p,2) = offsets(n)/100-0.01;
Dimitrios@0:                         nmat(p,3) = m;
Dimitrios@0:                     end;
Dimitrios@0:                 end;
Dimitrios@0:             end;
Dimitrios@0:             nmat = sortrows(nmat,1);
Dimitrios@0:             
Dimitrios@0:             
Dimitrios@0:             % Print output
Dimitrios@0:             if (i == length(AllnumBases))
Dimitrios@0:             	outputFileName = [outputFile(1:end-4) '_Bases_'  num2str(AllnumBases(i)) ...
Dimitrios@0:                 'individual_thres_' num2str(AllThres(j)) '_filt_' num2str(AllFiltering(k)) '.txt'];
Dimitrios@0:             else
Dimitrios@0:                 outputFileName = [outputFile(1:end-4) '_Bases_'  num2str(AllnumBases(i)) ...
Dimitrios@0:                 '_thres_' num2str(AllThres(j)) '_filt_' num2str(AllFiltering(k)) '.txt'];
Dimitrios@0:             end	    
Dimitrios@0:             fid=fopen(outputFileName,'w');
Dimitrios@0:             for m=1:size(nmat,1)
Dimitrios@0:                 fprintf(fid,'%.2f\t%.2f\t%s\n',nmat(m,1),nmat(m,2),Classes{nmat(m,3)});
Dimitrios@0:             end;
Dimitrios@0:             fclose(fid);
Dimitrios@0:             
Dimitrios@0:         end
Dimitrios@0:     end
Dimitrios@0:     
Dimitrios@0: end
Dimitrios@0: