comparison Problems/AMT_reconstruct.m @ 161:f42aa8bcb82f ivand_dev

debug and clean the SMALLbox Problems code

+function reconstructed=AMT_reconstruct(V, Problem)
+%% Reconstruction of midi file from representation in the given dictionary
+%   
+%   SMALL_midiGenerate is a part of SMALLbox and can be use to reconstruct
+%   a midi file given representation of the training set (V) in the
+%   dictionary Problem.A.
+%   Output is reconstructed structure with two fields:
+%   -   reconstructed.notes - matrix with transcribed notes
+%   -   reconstructed.midi - midi representation of transcription
+
+%
+%   Centre for Digital Music, Queen Mary, University of London.
+%   This file copyright 2009 Ivan Damnjanovic.
+%
+%   This program is free software; you can redistribute it and/or
+%   modify it under the terms of the GNU General Public License as
+%   published by the Free Software Foundation; either version 2 of the
+%   License, or (at your option) any later version.  See the file
+%   COPYING included with this distribution for more information.
+%%
+U=Problem.A;    %   Dictionary used for representation
+fs=Problem.fs;  %   Sampling rate
+f=Problem.f;    %   vector of frequencies at wihch spectrogram is computed
+
+ts=(Problem.windowSize*(1-Problem.overlap))/fs; %size of an analysis frame in seconds
+
+%%
+% Components pitch estimation using modified SWIPE algorithm by Arthuro
+% Camacho
+% 
+% Columns of matrix U are spectrograms of the notes learned from the
+% training set. We are estimating pitches of these notes by also
+% restricting pitch values to the one of the 88 piano notes. 
+
+pitch=zeros(size(U,2),1);
+
+for i=1:size(U,2)
+    
+    pitch(i) = SMALL_swipe(U(:,i),fs, f, [27.50 8192], 1/12);
+    
+end
+
+%%
+% If some of columns of U have the same pitch, their contribution to the
+% score (matrix V) is summed.
+
+[Ps,idx]=sort(pitch);
+ndp=1;
+Pd(ndp)=Ps(1);
+Vnew(ndp,:)=V(idx(1),:);
+for i=2:88
+    if Ps(i)> Ps(i-1)
+        
+        ndp=ndp+1;
+        Vnew(ndp,:)=V(idx(i),:);
+        Pd(ndp)=Ps(i);
+        
+    else
+        Vnew(ndp,:)=Vnew(ndp,:)+V(idx(i),:);
+    end
+end
+%%
+% Generate midi matrix
+
+midx=0;
+for i=1:ndp
+    
+    %   Threshold for finding onsets and offsets of notes
+    
+    thr=mean(Vnew(i,:));%+std(Vnew(i,:));
+    
+    if(Pd(i)~=0)
+        for j=1:size(Vnew,2)
+            if Vnew(i,j)<thr
+                Vnew(i,j)=0;
+                if(j>1)
+                    if (Vnew(i,j-1)==1)
+                        try
+                            M(midx,6)=(j-1)*ts;
+                            if (M(midx,6)-M(midx,5))<2*ts
+                                midx=midx-1;
+                            end
+                        catch
+                            pause;
+                        end
+                    end
+                end
+            else
+                Vnew(i,j)=1;
+                if(j>1)
+                    if (Vnew(i,j-1)==0)
+                        midx=midx+1;
+                        M(midx,1)=1;
+                        M(midx,2)=1;
+                        M(midx,3)=69 +round( 12 *log2(Pd(i)/440));
+                        M(midx,4)=80;
+                        M(midx,5)=(j-1)*ts;
+                    end
+                else
+                    midx=midx+1;
+                    M(midx,1)=1;
+                    M(midx,2)=1;
+                    M(midx,3)=69 + round(12 *log2(Pd(i)/440));
+                    M(midx,4)=80;
+                    M(midx,5)=0;
+                end
+            end
+        end
+        if M(midx,6)==0
+            M(midx,6)=(j-1)*ts;
+        end
+    end
+end
+
+M=sortrows(M,5);
+reconstructed.notes=M;
+reconstructed.midi = matrix2midi(M);