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1 function data = generateAMT_Learning_Problem(nfft, windowSize, overlap)
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2 %%% Generate Automatic Music Transcription Problem
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3 % Ivan Damnjanovic 2010
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4 %
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5 %
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6 % generateAMT_Learning_Problem is a part of the SMALLbox and generates
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7 % a problem that can be used for comparison of Dictionary Learning/Sparse
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8 % Representation techniques in automatic music transcription scenario.
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9 % The function prompts a user for an audio file (mid, wav, mat) reads it
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10 % and generates a spectrogram given fft size (default nfft=4096), analysis
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11 % window size (windowSize=2822), and analysis window overlap (overlap =
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12 % 0.5).
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13 %
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14 % The output of the function is stucture with following fields:
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15 % b - matrix with magnitudes of the spectrogram
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16 % f - vector of frequencies at wihch spectrogram is computed
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17 % windowSize - analysis window size
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18 % overlap - analysis window overlap
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19 % fs - sampling frequency
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20 % m - number of frequenciy points in spectrogram
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21 % n - number of time points in the spectrogram
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22 % p - number of dictionary elements to be learned (eg 88 for piano)
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23 % notesOriginal - notes of the original audio to be used for
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24 % comparison (if midi of the original exists)
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25 % name - name of the audio file to transcribe
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26
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27 %%
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28 FS=filesep;
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29 if ~ exist( 'nfft', 'var' ) || isempty(nfft), nfft = 4096; end
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30 if ~ exist( 'windowSize', 'var' ) || isempty(windowSize), windowSize = 2822; end
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31 if ~ exist( 'overlap', 'var' ) || isempty(overlap), overlap = 0.5; end
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32
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33 %%
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34 %ask for file name
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35 TMPpath=pwd;
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36 [pathstr1, name, ext, versn] = fileparts(which('SMALLboxSetup.m'));
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37 cd([pathstr1,FS,'data',FS,'audio']);
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38 [filename,pathname] = uigetfile({'*.mat; *.mid; *.wav'},'Select a file to transcribe');
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39 [pathstr, name, ext, versn] = fileparts(filename);
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40 data.name=name;
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41
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42 data.notesOriginal=[];
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43
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44 if strcmp(ext,'.mid')
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45 midi=readmidi(filename);
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46 data.notesOriginal=midiInfo(midi);
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47 y=midi2audio(midi);
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48 wavwrite(y, 44100, 16, 'temp.wav');
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49 [x.signal, x.fs, x.nbits]=wavread('temp.wav');
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50 delete('temp.wav');
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51 elseif strcmp(ext,'.wav')
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52 cd([pathstr1,FS, 'data', FS, 'audio', FS, 'midi']);
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53 filename1=[name, '.mid'];
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54 if exist(filename1, 'file')
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55 midi=readmidi(filename1);
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56 data.notesOriginal=midiInfo(midi);
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57 end
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58 cd([pathstr1,FS, 'data', FS, 'audio', FS, 'wav']);
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59 [x.signal, x.fs, x.nbits]=wavread(filename);
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60 else
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61 cd([pathstr1,FS, 'data', FS, 'audio', FS, 'midi']);
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62 filename1=[name, '.mid'];
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63 if exist(filename1, 'file')
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64 midi=readmidi(filename1);
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65 data.notesOriginal=midiInfo(midi);
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66 end
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67 cd([pathstr1,FS, 'data', FS, 'audio', FS, 'mat']);
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68 x=load([pathname,filename]);
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69 end
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70 %%
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71 [X, frX]=spectrogram(x.signal, hanning(windowSize), overlap*windowSize, nfft, x.fs);
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72 %%
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73 data.b=abs(X);
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74 data.f=frX;
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75 data.windowSize=windowSize;
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76 data.overlap=overlap;
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77 data.fs=x.fs;
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78 data.m=size(X,1);
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79 data.n=size(X,2);
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80
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81 data.p=88; %number of dictionary elements (ie notes to recover)
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82 cd(TMPpath);
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83
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84 end
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