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1 % This is a script that reproduces the results of the following ISMIR paper:
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2 %
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3 % Smith, J. B. L., and E. Chew. 2013. A meta-analysis of the MIREX Structural
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4 % Segmentation task. Proceedings of the International Society for Music
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5 % Information Retrieval Conference. Curitiba, Brazil. 251–6.
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6 %
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7 % DO read the README.txt before running this file. Among other things, it will
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8 % explain that you must download some data and place it in the correct file
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9 % tree before this script will work.
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10 %
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11 % DO read the comments in this script before running it. You may want to run
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12 % it piece by piece in order to understand exactly what it is doing.
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13
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14
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15 %%
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16 % STEP 0: Set up parameters.
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17 % Name the MIREX datasets and algorithms desired.
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18 dsets = {'mrx09','mrx10_1','mrx10_2','sal'};
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19 algos = {'KSP1','KSP2','KSP3','MHRAF1','OYZS1','SBV1','SMGA1','SMGA2','SP1'};
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20
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21 % YOU MUST SET THE FOLLOWING PATH YOURSELF!
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22 % Set it to be the same as the path given at the top of '1-get_mirex_estimates.rb'.
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23 base_directory = '/Users/me/Desktop/MIREX_data';
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24 base_directory = '/Users/jordan/Desktop/MIREX_data';
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25
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26
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27 % You should get a copy of the evalution scripts in the Code.SoundSoftware
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28 % repository. Wherever you put it, set the following path accordingly:
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29 addpath('/Users/me/Desktop/whereiputmymatlabfiles/structural_analysis_evaluation')
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30 addpath('/Users/jordan/Documents/structural_analysis_evaluation')
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31
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32 % You should also, clearly, add the current path (where this file is):
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33 addpath('.')
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34
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35 % Check that we have access to the correct dependencies.
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36
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37 if exist('compare_structures.m')~=2,
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38 fprintf('I could not locate ''compare_structures.m'', part of the Structural Analysis Evaluation project. Please read the help for this file before proceeding.\n')
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39 end
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40 if exist('load_annotation.m')~=2,
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41 fprintf('I could not locate ''load_annotation.m'', part of the Structural Analysis Evaluation project. Please read the help for this file before proceeding.\n')
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42 end
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43 if exist('collect_all_mirex_annotations')~=2,
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44 fprintf('I could not locate ''collect_all_mirex_annotations.m'', which should be in the same folder as this file. Something really screwed up has happened, clearly! Please read the help for this file before proceeding.\n')
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45 end
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46
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47 %%
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48 % STEP 1: Download data from MIREX website:
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49 %
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50 % - Ground truth files
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51 % - Algorithm output
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52 % - Reported evaluation results
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53 % (See README.txt to see where to get this data.)
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54
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55
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56 %%
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57 % STEP 2: Import all this data into some Matlab structures.
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58 %
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59 % 1. Assemble MIREX ground truth file data in Matlab.
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60 [mirex_truth mirex_dset_origin] = collect_all_mirex_annotations(base_directory, dsets, algos);
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61 % 2. Assemble MIREX algorithm output data in Matlab.
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62 mirex_output = collect_all_mirex_algo_output_data(base_directory, dsets, algos);
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63 % 3. Assemble MIREX evaluation results in Matlab.
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64 mirex_results = collect_all_mirex_results(base_directory, dsets, algos);
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65 % 4. Download public repositories of annotations.
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66 % NB: You must do this manually, as per the README.
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67 % 5. Assemble public ground truth data in Matlab.
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68 [public_truth public_dset_origin] = collect_all_public_annotations(base_directory);
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69
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70
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71 %%
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72 % STEP 3: Match MIREX and public data.
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73 %
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74 % With this information, we can now easily search for matches between
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75 % MIREX and public ground truth.
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76 [pub2mir, mir2pub, P] = match_mirex_to_public_data(mirex_truth, public_truth, mirex_dset_origin, public_dset_origin);
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77 % If you have already done this, do not repeat this time-consuming step. Instead:
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78 % load match_mirex_to_public_data_results
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79
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80 %%
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81 % STEP 4: Compile datacubes
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82 % 1. Compute extra evaluation measures using MIREX algorithm output.
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83 % 2. Compute extra features of the annotations (song length, mean segment length, etc.).
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84 % 3. Put it all together in a giant MEGADATACUBE.
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85 [datacube newcube extracube indexing_info] = compile_datacubes(mirex_truth, ...
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86 mirex_dset_origin, public_truth, mirex_output, mirex_results, mir2pub);
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87 megadatacube = [datacube newcube extracube];
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88 % If you have already done this, do not repeat this time-consuming step. Instead:
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89 % load datacubes
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90
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91
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92 %%
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93 % Step 5: Do the statistics!
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94 % 1. Compute correlations between all these parameters.
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95 % 2. Display correlation figures.
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96 % 3. Display analysis result figure.
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97 do_correlation_analyses % this one is just a script because it does not return any values.
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98
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99 % You are now finished! |