Mercurial > hg > smallbox
view examples/AudioInpainting/Audio_Declipping_Example.m @ 155:b14209313ba4 ivand_dev
Integration of Majorization Minimisation Dictionary Learning
author | Ivan Damnjanovic lnx <ivan.damnjanovic@eecs.qmul.ac.uk> |
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date | Mon, 22 Aug 2011 11:46:35 +0100 |
parents | 0de08f68256b |
children | 8b3c71bb44eb |
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%% Audio Declipping Example % % Audio declipping is a problem proposed in Audio Inpaining Toolbox and % in [2]. This is an example of solving the problem with fast omp using % Gabor dictionary and ompGabor implemented in SMALLbox [1]. % % [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. % %% clear all; % Defining the solvers to test in Audio declipping scenario % First solver omp2 - DCT+DST dictionary with no additional constraints SMALL.solver(1) = SMALL_init_solver('ompbox', 'omp2', '', 0); SMALL.solver(1).add_constraints = 0; % Second solver omp2 - DCT+DST dictionary with additional constraints SMALL.solver(2) = SMALL_init_solver('ompbox', 'omp2', '', 0); SMALL.solver(2).add_constraints = 1; % Third solver omp2 - Gabor dictionary with no additional constraints SMALL.solver(3) = SMALL_init_solver('ompbox', 'omp2Gabor', '', 0); SMALL.solver(3).add_constraints = 0; % Fourth solver omp2- Gabor dictionary with no additional constraints SMALL.solver(4) = SMALL_init_solver('ompbox', 'omp2Gabor', '', 0); SMALL.solver(4).add_constraints = 1; % Defining the Problem structure SMALL.Problem = generateAudioDeclippingProblem('male01_8kHz', 0.6, 256, 0.5, @wRect, @wSine, @wRect, @Gabor_Dictionary, 2); for idxSolver = 1:4 fprintf('\nStarting Audio Declipping of %s... \n', SMALL.Problem.name); fprintf('\nClipping level %s... \n', SMALL.Problem.clippingLevel); start=cputime; tStart=tic; error2=0.001^2; coeffFrames = zeros(SMALL.Problem.p, SMALL.Problem.n); for i = 1:SMALL.Problem.n idx = find(SMALL.Problem.M(:,i)); if size(idx,1)==SMALL.Problem.m continue end Dict = SMALL.Problem.B(idx,:); wDict = 1./sqrt(diag(Dict'*Dict)); SMALL.Problem.A = Dict*diag(wDict); SMALL.Problem.b1 = SMALL.Problem.b(idx,i); % set solver parameters SMALL.solver(idxSolver).param=struct(... 'epsilon', error2*size(idx,1),... 'maxatoms', 128, ... 'profile', 'off'); % Find solution SMALL.solver(idxSolver)=SMALL_solve(SMALL.Problem, SMALL.solver(idxSolver)); % Refine solution with additional constraints for declipping scenario if (SMALL.solver(idxSolver).add_constraints) SMALL.solver(idxSolver)=CVX_add_const_Audio_declipping(... SMALL.Problem, SMALL.solver(idxSolver), i); end %% coeffFrames(:,i) = wDict .* SMALL.solver(idxSolver).solution; end %% Set reconstruction function SMALL.Problem.reconstruct=@(x) AudioDeclipping_reconstruct(x, SMALL.Problem); reconstructed=SMALL.Problem.reconstruct(coeffFrames); SMALL.Problem = rmfield(SMALL.Problem, 'reconstruct'); tElapsed=toc(tStart); SMALL.solver(idxSolver).time = cputime - start; fprintf('Solver %s finished task in %2f seconds (cpu time). \n', ... SMALL.solver(idxSolver).name, SMALL.solver(idxSolver).time); fprintf('Solver %s finished task in %2f seconds (tic-toc time). \n', ... SMALL.solver(idxSolver).name, tElapsed); %% Plot results xClipped = SMALL.Problem.clipped; xClean = SMALL.Problem.original; xEst1 = reconstructed.audioAllSamples; xEst2 = reconstructed.audioOnlyClipped; fs = SMALL.Problem.fs; figure hold on plot(xClipped,'r') plot(xClean) plot(xEst2,'--g') plot([1;length(xClipped)],[1;1]*[-1,1]*max(abs(xClipped)),':r') legend('Clipped','True solution','Estimate') end % % Normalized and save sounds % normX = 1.1*max(abs([xEst1(:);xEst2(:);xClean(:)])); % L = min([length(xEst2),length(xEst1),length(xClean),length(xEst1),length(xClipped)]); % xEst1 = xEst1(1:L)/normX; % xEst2 = xEst2(1:L)/normX; % xClipped = xClipped(1:L)/normX; % xClean = xClean(1:L)/normX; % wavwrite(xEst1,fs,[expParam.destDir 'xEst1.wav']); % wavwrite(xEst2,fs,[expParam.destDir 'xEst2.wav']); % wavwrite(xClipped,fs,[expParam.destDir 'xClipped.wav']); % wavwrite(xClean,fs,[expParam.destDir 'xClean.wav']);