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1 classdef MTTMixedFeatureStober11Slaney08GenreBasicSm < MTTAudioFeature & handle
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2 % ---
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3 %
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4 % The usual worklow for these features constist of three steps
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5 % 1. extract: extracts the basic single-file dependent features
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6 % 2. define_global_transform: calculates the global feature
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7 % transformation parameters
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8 % 3. finalise: applies the common transformations to a specific feature
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9 % ---
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10
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11 properties(Constant = true)
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12
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13 % svn hook
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14 my_revision = str2double(substr('$Rev: 638 $', 5, -1));
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15 end
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16
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17 properties
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18 % ---
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19 % Set default parameters
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20 % ---
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21 my_params = MTTAudioFeature.inherited_params(...
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22 'MTTMixedFeatureSlaney08GenreBasicSm', ...
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23 ... % ---
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24 ... % these are Stober11 parameters
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25 ... % ---
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26 'stob_lowaudio', 1, ...
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27 'stob_highaudio', 1, ... %
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28 'stob_tags', 1, ...
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29 'stob_norm', 1 ...
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30 ... % ---
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31 );
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32 end
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33
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34 % ---
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35 % member functions
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36 % ---
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37 methods
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38
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39 % ---
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40 % constructor: pointer to feature in database
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41 % ---
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42 function feature = MTTMixedFeatureStober11Slaney08GenreBasicSm(varargin)
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43
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44 feature = feature@MTTAudioFeature(varargin{:});
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45 end
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46
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47 % ---
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48 % extract feature data by combining genre adn stob features
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49 % ---
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50 function data = extract(feature, clip)
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51
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52 % ---
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53 % get Basic Summary audio features. this includes possible
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54 % local normalisations
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55 % ---
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56 stob = clip.features('MTTMixedFeatureStober11',feature.my_params);
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57
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58 % ---
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59 % get genre tag features
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60 % ---
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61 genrebasicsm = clip.features('MTTMixedFeatureSlaney08GenreBasicSm',feature.my_params);
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62
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63 % save to features data field
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64 data.stob = stob;
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65 data.tags = genrebasicsm;
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66
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67 % prepare field for final features
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68 data.final.vector = [];
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69 data.final.vector_info = struct();
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70 data.final.dim = 0;
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71
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72 % save info data
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73 data.info.type = 'MTTMixedFeatureStober11Slaney08GenreBasicSm';
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74 data.info.owner_id = clip.id;
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75 data.info.creatorrev = feature.my_revision;
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76
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77 % save parameters
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78 data.info.params = feature.my_params;
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79 end
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80
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81 function define_global_transform(features)
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82 % calculate and set normalization factors from the group of
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83 % input features. These features will be set for the full database
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84
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85 if numel(features) == 1
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86 error ('Insert feature array for this method');
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87 end
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88
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89 % ---
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90 % We collect all the relevant stob
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91 % features and get the transform on this basis.
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92 % ---
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93 for i = 1:numel(features)
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94 stob(i) = features(i).data.stob;
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95 end
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96
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97 % call the features own transsform function
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98 stob.define_global_transform();
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99
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100 % ---
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101 % We collect all the relevant genretag
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102 % features and get the transform on this basis.
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103 % ---
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104 for i = 1:numel(features)
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105 genrebasicsm(i) = features(i).data.tags;
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106 end
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107
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108 % call the features own transsform function
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109 genrebasicsm.define_global_transform();
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110
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111 % ---
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112 % set common feature values for mixed features
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113 % ---
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114 features(1).my_db.set_common([1]); %trivial common
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115 end
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116
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117
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118 function finalise(feature)
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119 % applies a final transformation and collects the
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120 % information of this feature within a single vector
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121 % see info for types in specific dimensions
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122
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123 for i = 1:numel(feature)
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124
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125 % check for neccesary parameters
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126 if isempty(feature(i).my_db.commondb)
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127
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128 error('Define the global transformation first');
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129 end
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130
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131 % ---
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132 % finalise audio feature and get vector
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133 % ---
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134 stob = feature(i).data.stob;
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135 stob.finalise();
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136
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137 % finalise tag features
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138 genrebasicsm = feature(i).data.tags;
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139 genrebasicsm.finalise();
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140
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141 % ---
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142 % final data assembly
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143 % ---
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144
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145 % concatenate vectors
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146 feature(i).data.final.vector = ...
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147 [stob.vector() ; genrebasicsm.vector()];
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148
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149 % add feature dimensions
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150 feature(i).data.final.dim = stob.dim + genrebasicsm.dim;
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151
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152 % concatenate labels
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153 feature(i).data.final.vector_info.labels = ...
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154 {stob.data.final.vector_info.labels{:}, ...
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155 genrebasicsm.data.final.vector_info.labels{:}};
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156 end
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157 end
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158
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159 % ---
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160 % destructor: do we really want to remove this
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161 % from the database? No, but
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162 % TODO: create marker for unused objects in db, and a cleanup
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163 % function
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164 % ---
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165 function delete(feature)
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166
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167 end
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168
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169 function visualise(feature)
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170 % ---
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171 % plots the different data types collected in this feature
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172 % ---
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173 for i = 1:numel(feature)
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174 clip = MTTClip(feature(i).owner_id());
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175 end
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176 end
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177 end
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178 end |