diff toolboxes/MIRtoolbox1.3.2/MIRToolbox/@mirmfcc/mirmfcc.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/MIRtoolbox1.3.2/MIRToolbox/@mirmfcc/mirmfcc.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,156 @@
+function varargout = mirmfcc(orig,varargin)
+%   c = mirmfcc(a) finds the Mel frequency cepstral coefficients (ceps),
+%       a numerical description of the spectrum envelope.
+%
+%   Requires the Auditory Toolbox.
+%
+%   Optional arguments:
+%       c = mirmfcc(...,'Rank',N) computes the coefficients of rank(s) N
+%           (default: N = 1:13).
+%   If a is a frame decomposition, the temporal evolution of the MFCC,
+%       along the successive frames, is returned. In this case, a second
+%       option is available:
+%       mirmfcc(...,'Delta',d) performs d temporal differentiations of
+%           the coefficients, also called delta-MFCC (for d = 1) or
+%           delta-delta-MFCC (for d = 2).
+%       mirmfcc(...,'Delta') corresponds to mirmfcc(...,'Delta',1)
+%   Optional arguments related to the delta computation:
+%       mirmfcc(...,'Radius',r) specifies, for each frame, the number of
+%           successive and previous neighbouring frames taken into
+%           consideration for the least-square approximation.
+%           Usually 1 or 2.
+%           Default value: 2.
+
+        nbbands.key = 'Bands';
+        nbbands.type = 'Integer';
+        nbbands.default = 40;
+    option.nbbands = nbbands;
+
+        rank.key = 'Rank';
+        rank.type = 'Integer';
+        rank.default = 1:13;
+    option.rank = rank; 
+        
+        delta.key = 'Delta';
+        delta.type = 'Integer';
+        delta.default = 0;
+        delta.keydefault = 1;
+    option.delta = delta;
+        
+        radius.key = 'Radius';
+        radius.type = 'Integer';
+        radius.default = 2;
+    option.radius = radius;
+        
+specif.option = option;
+     
+varargout = mirfunction(@mirmfcc,orig,varargin,nargout,specif,@init,@main);
+
+
+function [x type] = init(x,option)
+if isamir(x,'miraudio') || isamir(x,'mirspectrum')
+    x = mirspectrum(x,'Mel','log','Bands',option.nbbands);
+end
+type = 'mirmfcc';
+
+
+function c = main(orig,option,postoption)
+if iscell(orig)
+    orig = orig{1};
+end
+if isa(orig,'mirmfcc')
+    c = orig;
+    if option.rank
+        magn = get(c,'Data');
+        rank = get(c,'Rank');
+        for h = 1:length(magn)
+            for k = 1:length(magn{h})
+                m = magn{h}{k};
+                r = rank{h}{k};
+                r1 = r(:,1,1);
+                range = find(ismember(r1,option.rank));
+                magn{h}{k} = m(range,:,:);
+                rank{h}{k} = r(range,:,:);
+            end
+        end
+        c = set(c,'Data',magn,'Rank',rank);
+    end
+    c = modif(c,option);
+else
+    c.delta = 0;
+    %disp('Computing Mel frequency cepstral coefficients...');
+    e = get(orig,'Magnitude');
+
+    % The following is largely based on the source code from Auditory Toolbox 
+    % (A part that I could not call directly from MIRtoolbox)
+    
+    % (Malcolm Slaney, August 1993, (c) 1998 Interval Research Corporation)
+    
+    try
+        MakeERBFilters(1,1,1); % Just to be sure that the Auditory Toolbox is installed
+    catch
+        error(['ERROR IN MIRFILTERBANK: Auditory Toolbox needs to be installed.']);
+    end  
+    
+    dc = cell(1,length(e));
+    rk = cell(1,length(e));
+    for h = 1:length(e)
+        dc{h} = cell(1,length(e{h}));
+        rk{h} = cell(1,length(e{h}));
+        for i = 1:length(e{h})
+            ei = e{h}{i};
+            totalFilters = size(ei,3); %Number of mel bands.
+
+            % Figure out Discrete Cosine Transform.  We want a matrix
+            % dct(i,j) which is totalFilters x cepstralCoefficients in size.
+            % The i,j component is given by 
+            %                cos( i * (j+0.5)/totalFilters pi )
+            % where we have assumed that i and j start at 0.
+            mfccDCTMatrix = 1/sqrt(totalFilters/2)*...
+                            cos(option.rank' * ...
+                                (2*(0:(totalFilters-1))+1) * ...
+                                 pi/2/totalFilters);
+            rank0 = find(option.rank == 0);
+            mfccDCTMatrix(rank0,:) = mfccDCTMatrix(rank0,:) * sqrt(2)/2;
+            ceps = zeros(size(mfccDCTMatrix,1),size(ei,2));
+            for j = 1:size(ei,2)
+                ceps(:,j) = mfccDCTMatrix * permute(ei(1,j,:),[3 1 2]);
+            end
+            dc{h}{i} = ceps;
+            rk{h}{i} = repmat(option.rank(:),[1 size(ceps,2) size(ceps,3)]);
+        end
+    end
+    c = class(c,'mirmfcc',mirdata(orig));
+    c = purgedata(c);
+    c = set(c,'Title','MFCC','Abs','coefficient ranks','Ord','magnitude',...
+              'Data',dc,'Rank',rk);
+    c = modif(c,option);
+end
+c = {c orig};
+
+
+function c = modif(c,option)
+d = get(c,'Data');
+fp = get(c,'FramePos');
+t = get(c,'Title');
+if option.delta
+    M = option.radius;
+    for k = 1:option.delta
+        for h = 1:length(d)
+            for i = 1:length(d{h})
+                nc = size(d{h}{i},2)-2*M;
+                di = zeros(size(d{h}{i},1),nc);
+                for j = 1:M
+                    di = di + j * (d{h}{i}(:,M+j+(1:nc)) ...
+                                 - d{h}{i}(:,M-j+(1:nc)));
+                end
+                di = di / 2 / sum((1:M).^2); % MULTIPLY BY 2 INSTEAD OF SQUARE FOR NORMALIZATION ?
+                d{h}{i} = di;
+                fp{h}{i} = fp{h}{i}(:,M+1:end-M);
+            end
+        end
+        t = ['Delta-',t];
+    end
+end
+c = set(c,'Data',d,'FramePos',fp,'Delta',get(c,'Delta')+option.delta,...
+          'Title',t);
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