Mercurial > hg > smallbox
comparison examples/Automatic Music Transcription/SMALL_AMT_SPAMS_test.m @ 107:dab78a3598b6
changes to comments for couple of scripts
author | Ivan Damnjanovic lnx <ivan.damnjanovic@eecs.qmul.ac.uk> |
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date | Wed, 18 May 2011 11:50:12 +0100 |
parents | cbf3521c25eb |
children | 8e660fd14774 |
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85:fd1c32cda22c | 107:dab78a3598b6 |
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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 % |
12 % This file contains an example of how SMALLbox can be used to test diferent | 3 % This file contains an example of how SMALLbox can be used to test diferent |
13 % dictionary learning techniques in Automatic Music Transcription problem. | 4 % dictionary learning techniques in Automatic Music Transcription problem. |
14 % It calls generateAMT_Learning_Problem that will let you to choose midi, | 5 % It calls generateAMT_Learning_Problem that will let you to choose midi, |
15 % wave or mat file to be transcribe. If file is midi it will be first | 6 % wave or mat file to be transcribe. If file is midi it will be first |
16 % converted to wave and original midi file will be used for comparison with | 7 % converted to wave and original midi file will be used for comparison with |
17 % results of dictionary learning and reconstruction. | 8 % results of dictionary learning and reconstruction. |
18 % The function will generarte the Problem structure that is used to learn | 9 % The function will generarte the Problem structure that is used to learn |
19 % Problem.p notes spectrograms from training set Problem.b using | 10 % Problem.p notes spectrograms from training set Problem.b using |
20 % dictionary learning technique defined in DL structure. | 11 % dictionary learning technique defined in DL structure. |
12 | |
13 % | |
14 % Centre for Digital Music, Queen Mary, University of London. | |
15 % This file copyright 2010 Ivan Damnjanovic. | |
16 % | |
17 % This program is free software; you can redistribute it and/or | |
18 % modify it under the terms of the GNU General Public License as | |
19 % published by the Free Software Foundation; either version 2 of the | |
20 % License, or (at your option) any later version. See the file | |
21 % COPYING included with this distribution for more information. | |
21 % | 22 % |
22 %% | 23 %% |
23 | 24 |
24 clear; | 25 clear; |
25 | 26 |