comparison examples/Automatic Music Transcription/SMALL_AMT_KSVD_Sparsity_test.m @ 25:cbf3521c25eb

(none)
author idamnjanovic
date Tue, 27 Apr 2010 13:33:13 +0000
parents f72603404233
children 8e660fd14774
comparison
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24:fc395272d53e 25:cbf3521c25eb
1 %% DICTIONARY LEARNING FOR AUTOMATIC MUSIC TRANSCRIPTION EXAMPLE 1 1 %% DICTIONARY LEARNING FOR AUTOMATIC MUSIC TRANSCRIPTION EXAMPLE 1
2 %
3 % Centre for Digital Music, Queen Mary, University of London.
4 % This file copyright 2010 Ivan Damnjanovic.
5 %
6 % This program is free software; you can redistribute it and/or
7 % modify it under the terms of the GNU General Public License as
8 % published by the Free Software Foundation; either version 2 of the
9 % License, or (at your option) any later version. See the file
10 % COPYING included with this distribution for more information.
11 %
2 % This file contains an example of how SMALLbox can be used to test diferent 12 % This file contains an example of how SMALLbox can be used to test diferent
3 % dictionary learning techniques in Automatic Music Transcription problem. 13 % dictionary learning techniques in Automatic Music Transcription problem.
4 % It calls generateAMT_Learning_Problem that will let you to choose midi, 14 % It calls generateAMT_Learning_Problem that will let you to choose midi,
5 % wave or mat file to be transcribe. If file is midi it will be first 15 % wave or mat file to be transcribe. If file is midi it will be first
6 % converted to wave and original midi file will be used for comparison with 16 % converted to wave and original midi file will be used for comparison with
7 % results of dictionary learning and reconstruction. 17 % results of dictionary learning and reconstruction.
8 % The function will generarte the Problem structure that is used to learn 18 % The function will generarte the Problem structure that is used to learn
9 % Problem.p notes spectrograms from training set Problem.b using 19 % Problem.p notes spectrograms from training set Problem.b using
10 % dictionary learning technique defined in DL structure. 20 % dictionary learning technique defined in DL structure.
11 % 21 %
12 % Ivan Damnjanovic 2010
13 %% 22 %%
14 23
15 clear; 24 clear;
16 25
17 26