trainSAE_allsongs_chroma.m

clear 

addpath chroma-ansyn
addpath tool/
addpath tool/tf_agc
addpath minFunc

% wav file into patches
fs = 16000;1
Imitation_file=dir('covers_pairs/*.wav');
L_Imitation=length(Imitation_file);
cellrecording=cell(L_Imitation,1);
numSum=0;

for i=1:1:L_Imitation

    wav_Imitation=audioread(fullfile('covers_pairs',Imitation_file(i).name));
    Imitation_file(i).name
    b=beat2(wav_Imitation,fs)*fs;                                       %extract beats from sample
    for lenb=1:length(b)-1
        b_min(lenb) = (b(lenb+1)-b(lenb));                              %get min of beat sample difference
    end
    b_min = floor(min(b_min));
    b_min_list(i)=b_min;
    wav_Imitation = wav_Imitation(b(1):b(end-24));          %truncates wav file to first and last beat - 8 measures
    
    if mod(b_min,2) ~= 0                                                     %makes sure beat interval is even for smooth CQT
        b_min=b_min+1;
    end
    L_win=b_min;                                                                   %window size (patch size) = 1/4th note
    L_hop=floor(L_win/2);                                                     % hop size is 1/8th note
    len_wav=length(wav_Imitation);                                     %length of wav file
    intCHROMA_single = chromagram_IF(wav_Imitation,fs,b_min); 
    clear -except intCHROMA                                                 %clear full chromatogram for next iteration
    
    %create all possible transpositions of chroma features
    for i=1:12
        intCHROMA(12*i-11:12*i-i+1,:)=intCHROMA_single(i:12,:);
    end
    
    for i=2:12
        intCHROMA(12*i-i+2:12*i,:)=intCHROMA_single(1:i-1,:);
    end
    
    %patches
    patch_win=10;                                                            %number of cqt windows per patch
    len=size(intCHROMA,2);                                             %number of elements along x axis of spectrogram
    num=round(len);                                                          %number of patches for sae train. determines hop size. we have #patches = beats. so hop size = 1/4 note.
    numSum=numSum+num;
    cellpatch=cell(num,1);
    index=1:(len-patch_win);
    for j=1:1:num-patch_win
        cellpatch(j)={intCHROMA(:,index(j):index(j)+patch_win-1)};
    end
    patch1=cell2mat(cellpatch);
    patch1=round(255*patch1/max(max(patch1)));
    fprintf('>');
    if mod(i,20)==0
        fprintf('\n');
    end
    cellrecording(i)={patch1};
end

recording=cell2mat(cellrecording);

% Remove silence patches
input_fbins=size(intCHROMA,1);
[M,N]=size(recording);
num=M/input_fbins;
count=0;
for i=1:num
    patch=recording((i-1)*input_fbins+1:i*input_fbins,:);
    if rms(rms(patch))>0.01
        count=count+1;
    end
end
numAftRemv=count;
cellpatch=cell(numAftRemv,1);

count=0;
for i =1:num
    patch=recording((i-1)*input_fbins+1:i*input_fbins,:);
    if rms(rms(patch))>0.01
        count=count+1;
        cellpatch(count)={patch};
    end
end

recordingAftRemv=cell2mat(cellpatch);
save('dataAftRemv.mat','recordingAftRemv');

% train the SAE
visibleSize=1440; % number of input neurons of the 1st AE 
hiddenSizeL1=500;   % number of hidden neurons of the 1st AE 
hiddenSizeL2=100;   % number of hidden neurons of the 2nd AE
% sparsityParam=0.01; % desired average activation of the hidden units.
%                      % (This was denoted by the Greek alphabet rho, which looks like a lower-case "p"). 
lambda=0.0001;  % weight decay parameter  
% beta=3; % weight of sparsity penalty term
patches = sampleIMAGES_AftRemv_chroma;
trainSAE(visibleSize,hiddenSizeL1,hiddenSizeL2,lambda,patches);

test_final_allsongs_chroma