Mercurial > hg > smallbox
view Problems/generateAudioDeclippingProblem.m @ 163:855025f4c779 ivand_dev
renaiming small_cgp to small_pcgp
author | Ivan Damnjanovic lnx <ivan.damnjanovic@eecs.qmul.ac.uk> |
---|---|
date | Wed, 07 Sep 2011 14:16:50 +0100 |
parents | f42aa8bcb82f |
children | 9c418bea7f6a |
line wrap: on
line source
function data = generateAudioDeclippingProblem(soundfile, clippingLevel, windowSize, overlap, wa, ws, wd, Dict_fun, redundancyFactor) %% Generate Audio Declipping Problem % % generateAudioDeclippingProblem is part of the SMALLbox [1] and generates % Audio declipping is a problem proposed in Audio Inpaining Toolbox and % in [2]. % % The function takes as an optional input % soundfile - name of the file % clippingLevel - (default 0.6) % windowSize - 1D frame size (eg 512) % overlap - ammount of overlaping frames between 0 and 1 % wa,ws,wd - analisys, synthesis and dictionary window functions % % Dict_fun - function to be used to generate dictionary % redundancyFactor - overcompletness of dictionary (default 2) % % The function outputs the structure with following fields: % original - original signal % clipped - clipped signal % clipMask - mask indicating clipped samples % clippingLevel - (default 0.6) % Upper_Limit - maximum value of original data % fs - sample rate of the original signal in Hertz % nbits - the number of bits per sample % sigma - added noise level % B - dictionary to be used for sparse representation % M - measurement matrix (non-clipped data in b) % b - matrix of clipped frames % m - size od dictionary atom % n - number of frames to be represented % p - number of atoms in dictionary % windowSize - 1D frame size (eg 512) % overlap - ammount of overlaping frames between 0 and 1 % wa,ws, wd - analisys, synthesis and dictionary window functions % % [1] I. Damnjanovic, M. E. P. Davies, and M. P. Plumbley "SMALLbox - an % evaluation framework for sparse representations and dictionary % learning algorithms," V. Vigneron et al. (Eds.): LVA/ICA 2010, % Springer-Verlag, Berlin, Germany, LNCS 6365, pp. 418-425 % [2] A. Adler, V. Emiya, M. G. Jafari, M. Elad, R. Gribonval, and M. D. % Plumbley, “Audio Inpainting,” submitted to IEEE Trans. Audio, Speech, % and Lang. Proc., 2011, http://hal.inria.fr/inria-00577079/en/. % Centre for Digital Music, Queen Mary, University of London. % This file copyright 2011 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. % %% FS=filesep; TMPpath=pwd; if ~ exist( 'soundfile', 'var' ) || isempty(soundfile) %ask for file name [pathstr1, name, ext, versn] = fileparts(which('SMALLboxSetup.m')); cd([pathstr1,FS,'data',FS,'audio']); [filename,pathname] = uigetfile({'*.mat; *.mid; *.wav'},'Select a file to transcribe'); [pathstr, name, ext, versn] = fileparts(filename); data.name=name; if strcmp(ext,'.mid') midi=readmidi(filename); % data.notesOriginal=midiInfo(midi); y=midi2audio(midi); wavwrite(y, 44100, 16, 'temp.wav'); [x.signal, x.fs, x.nbits]=wavread('temp.wav'); delete('temp.wav'); elseif strcmp(ext,'.wav') % cd([pathstr1,FS, 'data', FS, 'audio', FS, 'midi']); % filename1=[name, '.mid']; % if exist(filename1, 'file') % midi=readmidi(filename1); % data.notesOriginal=midiInfo(midi); % end cd([pathstr1,FS, 'data', FS, 'audio', FS, 'wav']); [x.signal, x.fs, x.nbits]=wavread(filename); else % cd([pathstr1,FS, 'data', FS, 'audio', FS, 'midi']); % filename1=[name, '.mid']; % if exist(filename1, 'file') % midi=readmidi(filename1); % data.notesOriginal=midiInfo(midi); % end cd([pathstr1,FS, 'data', FS, 'audio', FS, 'mat']); x=load([pathname,filename]); end else [x.signal, x.fs, x.nbits]=wavread(soundfile); [pathstr, name, ext, versn] = fileparts(soundfile); data.name=name; end if ~ exist( 'clippingLevel', 'var' ) || isempty(clippingLevel), clippingLevel = 0.6; end if ~ exist( 'windowSize', 'var' ) || isempty(windowSize), windowSize = 256; end if ~ exist( 'overlap', 'var' ) || isempty(overlap), overlap = 0.5; end if ~ exist( 'wa', 'var' ) || isempty(wa), wa = @wRect; end % Analysis window if ~ exist( 'ws', 'var' ) || isempty(ws), ws = @wSine; end % Synthesis window if ~ exist( 'wd', 'var' ) || isempty(wd), wd = @wRect; end % Weighting window for dictionary atoms %% preparing signal [problemData, solutionData] = generateDeclippingProblem(x.signal,clippingLevel); x_clip = im2colstep(problemData.x,[windowSize 1],[overlap*windowSize 1]); x_clip= diag(wa(windowSize)) * x_clip; blkMask=im2colstep(double(~problemData.IMiss),[windowSize 1],[overlap*windowSize 1]); %% Building dictionary if ~exist( 'redundancyFactor', 'var' ) || isempty(redundancyFactor), redundancyFactor = 2; end % Weighting window for dictionary atoms if exist('Dict_fun', 'var')&&~isempty(Dict_fun) param=struct('N', windowSize, 'redundancyFactor', redundancyFactor, 'wd', wd); data.B = Dict_fun(param); end data.b = x_clip; data.M = blkMask; data.original = solutionData.xClean; data.clipped = problemData.x; data.clipMask = problemData.IMiss; data.clippingLevel = clippingLevel; data.windowSize = windowSize; data.overlap = overlap; data.ws = ws; data.wa = wa; data.wd = wd; data.fs = x.fs; data.nbits = x.nbits; data.Upper_Limit = max(solutionData.xClean); [data.m, data.n] = size(x_clip); data.p = windowSize*redundancyFactor; %number of dictionary elements cd(TMPpath); end