annotate Code/Classifiers/kmeans_Formants_Singing.m @ 4:92ca03a8fa99 tip

Update to ICASSP 2013 benchmark
author Dawn Black
date Wed, 13 Feb 2013 11:02:39 +0000
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Dawn@4 1 function [] = kmeans_Formants_Singing( varargin )
Dawn@4 2
Dawn@4 3 cd 'C:\Users\dawn\Dropbox\TestResults'
Dawn@4 4
Dawn@4 5 DEBUG = 0;
Dawn@4 6 % output results file name
Dawn@4 7 masterFileOutputID = fopen( 'kmeans_paper_SingingFormantsStats.txt', 'a' );
Dawn@4 8 % input results file name
Dawn@4 9 % inputFileName = 'paper_singingFormantsStats_ZhangShuo.txt';
Dawn@4 10 % inputFileName = 'paper_singingFormantsStats_WangXinnong.txt';
Dawn@4 11 inputFileName = 'paper_singingFormantsStats.txt';
Dawn@4 12
Dawn@4 13 % This function allows the user to stipulate which Singing voice LLD's they
Dawn@4 14 % wish to forward to a k-means classifier and produces a file of
Dawn@4 15 % performance characteristics. Input arguments stipulate the LLD's and
Dawn@4 16 % there is a choice of:-
Dawn@4 17 %
Dawn@4 18 % ---- PRAAT FORMANT MEASUREMENTS ----
Dawn@4 19 % '_Formant_Burg'
Dawn@4 20 % '_Formant_all'
Dawn@4 21 % '_Formant_robust'
Dawn@4 22 %
Dawn@4 23 % A text file entitled kmeans_Singing_LLD1name_LLD2name_ ... LLDNname.txt
Dawn@4 24 % is produced that contains the results of the k-mean classification for
Dawn@4 25 % the LLD's specified and named in the result document title.
Dawn@4 26
Dawn@4 27 fprintf( masterFileOutputID, '\n RESULTS FILE NAME: %s\n', inputFileName);
Dawn@4 28 inputFileID = fopen( inputFileName );
Dawn@4 29
Dawn@4 30 % get the column numbers of the results that we want to classify
Dawn@4 31
Dawn@4 32 % COLUMN NUMBER : METRIC
Dawn@4 33 %
Dawn@4 34 % ------------- BURG FORMANTS ---------------
Dawn@4 35 % 11 : Number of BURG formants listed = nBF
Dawn@4 36 %
Dawn@4 37 % THERE ARE CURRENTLY 24 MEASUREMENTS TAKEN FOR EACH FORMANT
Dawn@4 38 nMetrics = 24;
Dawn@4 39 %
Dawn@4 40 % 12 : mean frequency of the first BURG formant
Dawn@4 41 % 13 : variance of the first BURG formant
Dawn@4 42 % 14 : minimum frequency of the first BURG formant
Dawn@4 43 % 15 : maximum frequency of the first BURG formant
Dawn@4 44 % 16 : mean Frequency Derivative of the first BURG formant
Dawn@4 45 % 17 : varience of the Frequency Derivative of the first BURG formant
Dawn@4 46 % 18 : min of the Frequency Derivative of the first BURG formant
Dawn@4 47 % 19 : max of the Frequency Derivative of the first BURG formant
Dawn@4 48 % 20 : mean of the Frequency 2nd Derivative of the first BURG formant
Dawn@4 49 % 21 : varience of the Frequency 2nd Derivative of the first BURG formant
Dawn@4 50 % 22 : min of the Frequency 2nd Derivative of the first BURG formant
Dawn@4 51 % 23 : max of the Frequency 2nd Derivative of the first BURG formant
Dawn@4 52 % 24 : mean of the Bandwidth of the first BURG formant
Dawn@4 53 % 25 : varience of the Bandwidth of the first BURG formant
Dawn@4 54 % 26 : min of the Bandwidth of the first BURG formant
Dawn@4 55 % 27 : max of the Bandwidth of the first BURG formant
Dawn@4 56 % 28 : mean of the Bandwidth Derivative of the first BURG formant
Dawn@4 57 % 29 : varience of the Bandwidth Derivative of the first BURG formant
Dawn@4 58 % 30 : min of the Bandwidth Derivative of the first BURG formant
Dawn@4 59 % 31 : max of the Bandwidth Derivative of the first BURG formant
Dawn@4 60 % 32 : mean of the Bandwidth 2nd Derivative of the first BURG formant
Dawn@4 61 % 33 : var of the Bandwidth 2nd Derivative of the first BURG formant
Dawn@4 62 % 34 : min of the Bandwidth 2nd Derivative of the first BURG formant
Dawn@4 63 % 35 : max of the Bandwidth 2nd Derivative of the first BURG formant
Dawn@4 64 %
Dawn@4 65 % ....... there are nMetrics for each formant in nBF formants, so cycle
Dawn@4 66 % through until the last is reached ......
Dawn@4 67 %
Dawn@4 68 % 36 + ((nBF-1)*nMetrics) : mean frequency of the nBF BURG formant
Dawn@4 69 % 36 + ((nBF-1)*nMetrics) + 1 : variance of the nBF BURG formant
Dawn@4 70 % 36 + ((nBF-1)*nMetrics) + 2 : minimum frequency of the nBF BURG formant
Dawn@4 71 % 36 + ((nBF-1)*nMetrics) + 3 : maximum frequency of the nBF BURG formant
Dawn@4 72 % 36 + ((nBF-1)*nMetrics) + 4 : mean Frequency Derivative of the nBF BURG formant
Dawn@4 73 % 36 + ((nBF-1)*nMetrics) + 5 : varience of the Frequency Derivative of the nBF BURG formant
Dawn@4 74 % 36 + ((nBF-1)*nMetrics) + 6 : min of the Frequency Derivative of the nBF BURG formant
Dawn@4 75 % 36 + ((nBF-1)*nMetrics) + 7 : max of the Frequency Derivative of the nBF BURG formant
Dawn@4 76 % 36 + ((nBF-1)*nMetrics) + 8 : mean of the Frequency 2nd Derivative of the nBF BURG formant
Dawn@4 77 % 36 + ((nBF-1)*nMetrics) + 9 : varience of the Frequency 2nd Derivative of the nBF BURG formant
Dawn@4 78 % 36 + ((nBF-1)*nMetrics) + 10 : min of the Frequency 2nd Derivative of the nBF BURG formant
Dawn@4 79 % 36 + ((nBF-1)*nMetrics) + 11 : max of the Frequency 2nd Derivative of the nBF BURG formant
Dawn@4 80 % 36 + ((nBF-1)*nMetrics) + 12 : mean of the Bandwidth of the nBF BURG formant
Dawn@4 81 % 36 + ((nBF-1)*nMetrics) + 13 : varience of the Bandwidth of the nBF BURG formant
Dawn@4 82 % 36 + ((nBF-1)*nMetrics) + 14 : min of the Bandwidth of the nBF BURG formant
Dawn@4 83 % 36 + ((nBF-1)*nMetrics) + 15 : max of the Bandwidth of the nBF BURG formant
Dawn@4 84 % 36 + ((nBF-1)*nMetrics) + 16 : mean of the Bandwidth Derivative of the nBF BURG formant
Dawn@4 85 % 36 + ((nBF-1)*nMetrics) + 17 : variece of the Bandwidth Derivative of the nBF BURG formant
Dawn@4 86 % 36 + ((nBF-1)*nMetrics) + 18 : min of the Bandwidth Derivative of the nBF BURG formant
Dawn@4 87 % 36 + ((nBF-1)*nMetrics) + 19 : max of the Bandwidth Derivative of the nBF BURG formant
Dawn@4 88 % 36 + ((nBF-1)*nMetrics) + 20 : mean of the Bandwidth 2nd Derivative of the nBF BURG formant
Dawn@4 89 % 36 + ((nBF-1)*nMetrics) + 21 : var of the Bandwidth 2nd Derivative of the nBF BURG formant
Dawn@4 90 % 36 + ((nBF-1)*nMetrics) + 22 : min of the Bandwidth 2nd Derivative of the nBF BURG formant
Dawn@4 91 % 36 + ((nBF-1)*nMetrics) + 23 : max of the Bandwidth 2nd Derivative of the nBF BURG formant
Dawn@4 92 %
Dawn@4 93 % FOR THE MEAN OF ALL BURG FORMANTS
Dawn@4 94 % 36 + (nBF*nMetrics) : mean of all formants Frequency
Dawn@4 95 % 36 + (nBF*nMetrics) + 1 : varience of the mean of all formants Frequency
Dawn@4 96 % 36 + (nBF*nMetrics) + 2 : minimum of the mean of all formants Frequency
Dawn@4 97 % 36 + (nBF*nMetrics) + 3 : maximum of the mean of all formants Frequency
Dawn@4 98 % 36 + (nBF*nMetrics) + 4 : mean of all formants mean Frequency Derivative
Dawn@4 99 % 36 + (nBF*nMetrics) + 5 : mean of all formants varience Frequency Derivative
Dawn@4 100 % 36 + (nBF*nMetrics) + 6 : min of the mean of all formants Frequency Derivative
Dawn@4 101 % 36 + (nBF*nMetrics) + 7 : max of the mean of all formants Frequency Derivative
Dawn@4 102 % 36 + (nBF*nMetrics) + 8 : mean of the mean of all formants Frequency 2nd Derivative
Dawn@4 103 % 36 + (nBF*nMetrics) + 9 : varience of the mean of all formants Frequency 2nd Derivative
Dawn@4 104 % 36 + (nBF*nMetrics) + 10 : min of the mean of all formants Frequency 2nd Derivative
Dawn@4 105 % 36 + (nBF*nMetrics) + 11 : max of the mean of all formants Frequency 2nd Derivative
Dawn@4 106 %
Dawn@4 107 % ------------- ALL FORMANTS ---------------
Dawn@4 108 %
Dawn@4 109 % 36 + (nBF*nMetrics) + 12 : Number of ALL formants listed = nAF
Dawn@4 110 %
Dawn@4 111 % startOfALLMeasurements = 36 + (nBF*nMetrics) + 13;
Dawn@4 112 %
Dawn@4 113 % startOfALLMeasurements : mean frequency of the first ALL formant
Dawn@4 114 % startOfALLMeasurements + 1 : variance of the first ALL formant
Dawn@4 115 % startOfALLMeasurements + 2 : minimum frequency of the first ALL formant
Dawn@4 116 % startOfALLMeasurements + 3 : maximum frequency of the first ALL formant
Dawn@4 117 % startOfALLMeasurements + 4 : mean Frequency Derivative of the first ALL formant
Dawn@4 118 % startOfALLMeasurements + 5 : varience of the Frequency Derivative of the first ALL formant
Dawn@4 119 % startOfALLMeasurements + 6 : min of the Frequency Derivative of the first ALL formant
Dawn@4 120 % startOfALLMeasurements + 7 : max of the Frequency Derivative of the first ALL formant
Dawn@4 121 % startOfALLMeasurements + 8 : mean of the Frequency 2nd Derivative of the first ALL formant
Dawn@4 122 % startOfALLMeasurements + 9 : varience of the Frequency 2nd Derivative of the first ALL formant
Dawn@4 123 % startOfALLMeasurements + 10 : min of the Frequency 2nd Derivative of the first ALL formant
Dawn@4 124 % startOfALLMeasurements + 11 : max of the Frequency 2nd Derivative of the first ALL formant
Dawn@4 125 % startOfALLMeasurements + 12 : mean of the Bandwidth of the first ALL formant
Dawn@4 126 % startOfALLMeasurements + 13 : varience of the Bandwidth of the first ALL formant
Dawn@4 127 % startOfALLMeasurements + 14 : min of the Bandwidth of the first ALL formant
Dawn@4 128 % startOfALLMeasurements + 15 : max of the Bandwidth of the first ALL formant
Dawn@4 129 % startOfALLMeasurements + 16 : mean of the Bandwidth Derivative of the first ALL formant
Dawn@4 130 % startOfALLMeasurements + 17 : varience of the Bandwidth Derivative of the first ALL formant
Dawn@4 131 % startOfALLMeasurements + 18 : min of the Bandwidth Derivative of the first ALL formant
Dawn@4 132 % startOfALLMeasurements + 19 : max of the Bandwidth Derivative of the first ALL formant
Dawn@4 133 % startOfALLMeasurements + 20 : mean of the Bandwidth 2nd Derivative of the first ALL formant
Dawn@4 134 % startOfALLMeasurements + 21 : var of the Bandwidth 2nd Derivative of the first ALL formant
Dawn@4 135 % startOfALLMeasurements + 22 : min of the Bandwidth 2nd Derivative of the first ALL formant
Dawn@4 136 % startOfALLMeasurements + 23 : max of the Bandwidth 2nd Derivative of the first ALL formant
Dawn@4 137 %
Dawn@4 138 % ....... there are nMetrics for each formant in nAF formants, so cycle
Dawn@4 139 % through until the last is reached ......
Dawn@4 140 %
Dawn@4 141 % startOfALLMeasurements + ((nAF-1)*nMetrics) : mean frequency of the nAF ALL formant
Dawn@4 142 % startOfALLMeasurements + ((nAF-1)*nMetrics) : variance of the nAF ALL formant
Dawn@4 143 % startOfALLMeasurements + ((nAF-1)*nMetrics) : minimum frequency of the nAF ALL formant
Dawn@4 144 % startOfALLMeasurements + ((nAF-1)*nMetrics) : maximum frequency of the nAF ALL formant
Dawn@4 145 % startOfALLMeasurements + ((nAF-1)*nMetrics) : mean Frequency Derivative of the nAF ALL formant
Dawn@4 146 % startOfALLMeasurements + ((nAF-1)*nMetrics) : varience of the Frequency Derivative of the nAF ALL formant
Dawn@4 147 % startOfALLMeasurements + ((nAF-1)*nMetrics) : min of the Frequency Derivative of the nAF ALL formant
Dawn@4 148 % startOfALLMeasurements + ((nAF-1)*nMetrics) : max of the Frequency Derivative of the nAF ALL formant
Dawn@4 149 % startOfALLMeasurements + ((nAF-1)*nMetrics) : mean of the Frequency 2nd Derivative of the nAF ALL formant
Dawn@4 150 % startOfALLMeasurements + ((nAF-1)*nMetrics) : varience of the Frequency 2nd Derivative of the nAF ALL formant
Dawn@4 151 % startOfALLMeasurements + ((nAF-1)*nMetrics) : min of the Frequency 2nd Derivative of the nAF ALL formant
Dawn@4 152 % startOfALLMeasurements + ((nAF-1)*nMetrics) : max of the Frequency 2nd Derivative of the nAF ALL formant
Dawn@4 153 % startOfALLMeasurements + ((nAF-1)*nMetrics) : mean of the Bandwidth of the nAF ALL formant
Dawn@4 154 % startOfALLMeasurements + ((nAF-1)*nMetrics) : varience of the Bandwidth of the nAF ALL formant
Dawn@4 155 % startOfALLMeasurements + ((nAF-1)*nMetrics) : min of the Bandwidth of the nAF ALL formant
Dawn@4 156 % startOfALLMeasurements + ((nAF-1)*nMetrics) : max of the Bandwidth of the nAF ALL formant
Dawn@4 157 % startOfALLMeasurements + ((nAF-1)*nMetrics) : mean of the Bandwidth Derivative of the nAF ALL formant
Dawn@4 158 % startOfALLMeasurements + ((nAF-1)*nMetrics) : variece of the Bandwidth Derivative of the nAF ALL formant
Dawn@4 159 % startOfALLMeasurements + ((nAF-1)*nMetrics) : min of the Bandwidth Derivative of the nAF ALL formant
Dawn@4 160 % startOfALLMeasurements + ((nAF-1)*nMetrics) : max of the Bandwidth Derivative of the nAF ALL formant
Dawn@4 161 % startOfALLMeasurements + ((nAF-1)*nMetrics) : mean of the Bandwidth 2nd Derivative of the nAF ALL formant
Dawn@4 162 % startOfALLMeasurements + ((nAF-1)*nMetrics) : var of the Bandwidth 2nd Derivative of the nAF ALL formant
Dawn@4 163 % startOfALLMeasurements + ((nAF-1)*nMetrics) : min of the Bandwidth 2nd Derivative of the nAF ALL formant
Dawn@4 164 % startOfALLMeasurements + ((nAF-1)*nMetrics) : max of the Bandwidth 2nd Derivative of the nAF ALL formant
Dawn@4 165 %
Dawn@4 166 % FOR THE MEAN OF ALL ALL FORMANTS
Dawn@4 167 % startOfALLMeasurements + (nAF*nMetrics) : mean of all formants Frequency
Dawn@4 168 % startOfALLMeasurements + (nAF*nMetrics) + 1 : varience of the mean of all formants Frequency
Dawn@4 169 % startOfALLMeasurements + (nAF*nMetrics) + 2 : minimum of the mean of all formants Frequency
Dawn@4 170 % startOfALLMeasurements + (nAF*nMetrics) + 3 : maximum of the mean of all formants Frequency
Dawn@4 171 % startOfALLMeasurements + (nAF*nMetrics) + 4 : mean of all formants mean Frequency Derivative
Dawn@4 172 % startOfALLMeasurements + (nAF*nMetrics) + 5 : mean of all formants varience Frequency Derivative
Dawn@4 173 % startOfALLMeasurements + (nAF*nMetrics) + 6 : min of the mean of all formants Frequency Derivative
Dawn@4 174 % startOfALLMeasurements + (nAF*nMetrics) + 7 : max of the mean of all formants Frequency Derivative
Dawn@4 175 % startOfALLMeasurements + (nAF*nMetrics) + 8 : mean of the mean of all formants Frequency 2nd Derivative
Dawn@4 176 % startOfALLMeasurements + (nAF*nMetrics) + 9 : varience of the mean of all formants Frequency 2nd Derivative
Dawn@4 177 % startOfALLMeasurements + (nAF*nMetrics) + 10 : min of the mean of all formants Frequency 2nd Derivative
Dawn@4 178 % startOfALLMeasurements + (nAF*nMetrics) + 11 : max of the mean of all formants Frequency 2nd Derivative
Dawn@4 179 %
Dawn@4 180 % ------------- ROBUST FORMANTS ---------------
Dawn@4 181 %
Dawn@4 182 % startOfALLMeasurements + (nAF*nMetrics) + 12 : Number of ROBUST formants listed = nRF
Dawn@4 183 %
Dawn@4 184 % startOfROBUSTMeasurements = startOfALLMeasurements + (nAF*nMetrics) + 13;
Dawn@4 185 %
Dawn@4 186 % startOfROBUSTMeasurements : mean frequency of the first ROBUST formant
Dawn@4 187 % startOfROBUSTMeasurements + 1 : variance of the first ROBUST formant
Dawn@4 188 % startOfROBUSTMeasurements + 2 : minimum frequency of the first ROBUST formant
Dawn@4 189 % startOfROBUSTMeasurements + 3 : maximum frequency of the first ROBUST formant
Dawn@4 190 % startOfROBUSTMeasurements + 4 : mean Frequency Derivative of the first ROBUST formant
Dawn@4 191 % startOfROBUSTMeasurements + 5 : varience of the Frequency Derivative of the first ROBUST formant
Dawn@4 192 % startOfROBUSTMeasurements + 6 : min of the Frequency Derivative of the first ROBUST formant
Dawn@4 193 % startOfROBUSTMeasurements + 7 : max of the Frequency Derivative of the first ROBUST formant
Dawn@4 194 % startOfROBUSTMeasurements + 8 : mean of the Frequency 2nd Derivative of the first ROBUST formant
Dawn@4 195 % startOfROBUSTMeasurements + 9 : varience of the Frequency 2nd Derivative of the first ROBUST formant
Dawn@4 196 % startOfROBUSTMeasurements + 10 : min of the Frequency 2nd Derivative of the first ROBUST formant
Dawn@4 197 % startOfROBUSTMeasurements + 11 : max of the Frequency 2nd Derivative of the first ROBUST formant
Dawn@4 198 % startOfROBUSTMeasurements + 12 : mean of the Bandwidth of the first ROBUST formant
Dawn@4 199 % startOfROBUSTMeasurements + 13 : varience of the Bandwidth of the first ROBUST formant
Dawn@4 200 % startOfROBUSTMeasurements + 14 : min of the Bandwidth of the first ROBUST formant
Dawn@4 201 % startOfROBUSTMeasurements + 15 : max of the Bandwidth of the first ROBUST formant
Dawn@4 202 % startOfROBUSTMeasurements + 16 : mean of the Bandwidth Derivative of the first ROBUST formant
Dawn@4 203 % startOfROBUSTMeasurements + 17 : varience of the Bandwidth Derivative of the first ROBUST formant
Dawn@4 204 % startOfROBUSTMeasurements + 18 : min of the Bandwidth Derivative of the first ROBUST formant
Dawn@4 205 % startOfROBUSTMeasurements + 19 : max of the Bandwidth Derivative of the first ROBUST formant
Dawn@4 206 % startOfROBUSTMeasurements + 20 : mean of the Bandwidth 2nd Derivative of the first ROBUST formant
Dawn@4 207 % startOfROBUSTMeasurements + 21 : var of the Bandwidth 2nd Derivative of the first ROBUST formant
Dawn@4 208 % startOfROBUSTMeasurements + 22 : min of the Bandwidth 2nd Derivative of the first ROBUST formant
Dawn@4 209 % startOfROBUSTMeasurements + 23 : max of the Bandwidth 2nd Derivative of the first ROBUST formant
Dawn@4 210 %
Dawn@4 211 % ....... there are nMetrics for each formant in nRF formants, so cycle
Dawn@4 212 % through until the last is reached ......
Dawn@4 213 %
Dawn@4 214 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : mean frequency of the nRF ROBUST formant
Dawn@4 215 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : variance of the nRF ROBUST formant
Dawn@4 216 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : minimum frequency of the nRF ROBUST formant
Dawn@4 217 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : maximum frequency of the nRF ROBUST formant
Dawn@4 218 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : mean Frequency Derivative of the nRF ROBUST formant
Dawn@4 219 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : varience of the Frequency Derivative of the nRF ROBUST formant
Dawn@4 220 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : min of the Frequency Derivative of the nRF ROBUST formant
Dawn@4 221 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : max of the Frequency Derivative of the nRF ROBUST formant
Dawn@4 222 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : mean of the Frequency 2nd Derivative of the nRF ROBUST formant
Dawn@4 223 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : varience of the Frequency 2nd Derivative of the nRF ROBUST formant
Dawn@4 224 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : min of the Frequency 2nd Derivative of the nRF ROBUST formant
Dawn@4 225 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : max of the Frequency 2nd Derivative of the nRF ROBUST formant
Dawn@4 226 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : mean of the Bandwidth of the nRF ROBUST formant
Dawn@4 227 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : varience of the Bandwidth of the nRF ROBUST formant
Dawn@4 228 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : min of the Bandwidth of the nRF ROBUST formant
Dawn@4 229 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : max of the Bandwidth of the nRF ROBUST formant
Dawn@4 230 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : mean of the Bandwidth Derivative of the nRF ROBUST formant
Dawn@4 231 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : variece of the Bandwidth Derivative of the nRF ROBUST formant
Dawn@4 232 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : min of the Bandwidth Derivative of the nRF ROBUST formant
Dawn@4 233 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : max of the Bandwidth Derivative of the nRF ROBUST formant
Dawn@4 234 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : mean of the Bandwidth 2nd Derivative of the nRF ROBUST formant
Dawn@4 235 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : var of the Bandwidth 2nd Derivative of the nRF ROBUST formant
Dawn@4 236 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : min of the Bandwidth 2nd Derivative of the nRF ROBUST formant
Dawn@4 237 % startOfROBUSTMeasurements + ((nRF-1)*nMetrics) : max of the Bandwidth 2nd Derivative of the nRF ROBUST formant
Dawn@4 238 %
Dawn@4 239 % FOR THE MEAN OF ALL ROBUST FORMANTS
Dawn@4 240 % startOfROBUSTMeasurements + (nRF*nMetrics) : mean of all formants Frequency
Dawn@4 241 % startOfROBUSTMeasurements + (nRF*nMetrics) + 1 : varience of the mean of all formants Frequency
Dawn@4 242 % startOfROBUSTMeasurements + (nRF*nMetrics) + 2 : minimum of the mean of all formants Frequency
Dawn@4 243 % startOfROBUSTMeasurements + (nRF*nMetrics) + 3 : maximum of the mean of all formants Frequency
Dawn@4 244 % startOfROBUSTMeasurements + (nRF*nMetrics) + 4 : mean of all formants mean Frequency Derivative
Dawn@4 245 % startOfROBUSTMeasurements + (nRF*nMetrics) + 5 : mean of all formants varience Frequency Derivative
Dawn@4 246 % startOfROBUSTMeasurements + (nRF*nMetrics) + 6 : min of the mean of all formants Frequency Derivative
Dawn@4 247 % startOfROBUSTMeasurements + (nRF*nMetrics) + 7 : max of the mean of all formants Frequency Derivative
Dawn@4 248 % startOfROBUSTMeasurements + (nRF*nMetrics) + 8 : mean of the mean of all formants Frequency 2nd Derivative
Dawn@4 249 % startOfROBUSTMeasurements + (nRF*nMetrics) + 9 : varience of the mean of all formants Frequency 2nd Derivative
Dawn@4 250 % startOfROBUSTMeasurements + (nRF*nMetrics) + 10 : min of the mean of all formants Frequency 2nd Derivative
Dawn@4 251 % startOfROBUSTMeasurements + (nRF*nMetrics) + 11 : max of the mean of all formants Frequency 2nd Derivative
Dawn@4 252 %
Dawn@4 253
Dawn@4 254 noOfArguments = length(varargin);
Dawn@4 255 columnIndices = [];
Dawn@4 256
Dawn@4 257 getBURGFormants = 0;
Dawn@4 258 getAllFormants=0;
Dawn@4 259 getRobustFormants=0;
Dawn@4 260
Dawn@4 261 for i=1 : noOfArguments
Dawn@4 262 if( strcmp( varargin{i}, 'formant_Burg' ))
Dawn@4 263 getBURGFormants = 1;
Dawn@4 264 elseif( strcmp( varargin{i}, 'formant_all' ))
Dawn@4 265 getAllFormants=1;
Dawn@4 266 elseif( strcmp( varargin{i}, 'formant_robust' ))
Dawn@4 267 getRobustFormants=1;
Dawn@4 268 end
Dawn@4 269 end
Dawn@4 270
Dawn@4 271 titleName = '';
Dawn@4 272 for i=1 : noOfArguments
Dawn@4 273 titleName = [ titleName varargin{i} '_'];
Dawn@4 274 fprintf( masterFileOutputID, '%s_', varargin{i} );
Dawn@4 275 end
Dawn@4 276
Dawn@4 277 fprintf( masterFileOutputID, '\t' );
Dawn@4 278
Dawn@4 279 % -------------------- get the data from the results file ---------------
Dawn@4 280 lineCount = 0;
Dawn@4 281 fileCount = 0;
Dawn@4 282 data = [];
Dawn@4 283 while( ~(feof(inputFileID)) )
Dawn@4 284
Dawn@4 285 outputValues = [];
Dawn@4 286 % sampleEmotion = [];
Dawn@4 287 % gender = [];
Dawn@4 288
Dawn@4 289 thestr = fgetl(inputFileID);
Dawn@4 290 if( lineCount > 10 ) % skip the file header
Dawn@4 291 fileCount = fileCount + 1;
Dawn@4 292
Dawn@4 293 % determine whether we have a positive or negative sample
Dawn@4 294 sampleEmotion( fileCount ) = 'U';
Dawn@4 295 if( ~(isempty(strfind(thestr,'pos'))))
Dawn@4 296 % sample is positive
Dawn@4 297 sampleEmotion( fileCount ) = 'P';
Dawn@4 298 elseif( ~(isempty(strfind(thestr,'neg'))))
Dawn@4 299 % sample is negative
Dawn@4 300 sampleEmotion( fileCount ) = 'N';
Dawn@4 301 else
Dawn@4 302 disp('EEEK!');
Dawn@4 303 pause;
Dawn@4 304 end
Dawn@4 305
Dawn@4 306 % % determine whether we have a male, female or trans sample
Dawn@4 307 % gender( fileCount ) = '?';
Dawn@4 308 % if( ~(isempty(strfind(thestr,'fem'))))
Dawn@4 309 % % gender is female
Dawn@4 310 % gender( fileCount ) = 'F';
Dawn@4 311 % elseif( ~(isempty(strfind(thestr,'male'))))
Dawn@4 312 % % gender is male
Dawn@4 313 % gender( fileCount ) = 'M';
Dawn@4 314 % elseif( ~(isempty(strfind(thestr,'trans'))))
Dawn@4 315 % % gender is trans
Dawn@4 316 % gender( fileCount ) = 'T';
Dawn@4 317 % else
Dawn@4 318 % disp('EEEK!');
Dawn@4 319 % pause;
Dawn@4 320 % end
Dawn@4 321
Dawn@4 322 %how many values are in the string?
Dawn@4 323 spaces = strfind( thestr, ' ' );
Dawn@4 324 numberstr = thestr( spaces(1) : end ); % chop off the file name
Dawn@4 325 frmtpos = strfind( numberstr, 'maxNoOfFormants'); % find the position of the label for number of formants
Dawn@4 326
Dawn@4 327 % str1 = numberstr( 1 : frmtpos(1)-1 ); % string contains jitter and shimmer values
Dawn@4 328 str2 = numberstr( frmtpos(1) : frmtpos(2)-1 ); % string contains all BURG formant information
Dawn@4 329 str3 = numberstr( frmtpos(2) : frmtpos(3)-1 ); % string contains all ALL formant information
Dawn@4 330 str4 = numberstr( frmtpos(3) : end ); % string contains all ROBUST formant information
Dawn@4 331
Dawn@4 332
Dawn@4 333 % vars = sscanf( str1, '%f', inf );
Dawn@4 334 % % extract the shimmer and jitter values
Dawn@4 335 % outputValues = [ outputValues vars( columnIndices )'];
Dawn@4 336
Dawn@4 337 if( getBURGFormants )
Dawn@4 338 spaces = strfind( str2, ' ' ); % remove the string 'maxNoOfFormants'
Dawn@4 339 vars = sscanf( str2( spaces(1) : end ), '%f', inf );
Dawn@4 340 outputValues = stripOutFormantValues( vars, outputValues );
Dawn@4 341 end
Dawn@4 342
Dawn@4 343 if( getAllFormants )
Dawn@4 344 spaces = strfind( str3, ' ' ); % remove the string 'maxNoOfFormants'
Dawn@4 345 vars = sscanf( str3( spaces(1) : end ), '%f', inf );
Dawn@4 346 outputValues = stripOutFormantValues( vars, outputValues );
Dawn@4 347 end
Dawn@4 348
Dawn@4 349 if( getRobustFormants )
Dawn@4 350 spaces = strfind( str4, ' ' ); % remove the string 'maxNoOfFormants'
Dawn@4 351 vars = sscanf( str4( spaces(1) : end ), '%f', inf );
Dawn@4 352 outputValues = stripOutFormantValues( vars, outputValues );
Dawn@4 353 end
Dawn@4 354
Dawn@4 355 [m n] = size( data );
Dawn@4 356 % sometimes the 'all' formants command gives us fewer formants than
Dawn@4 357 % usual. If this is the case,then we will have to pad with zeros
Dawn@4 358 % for now.
Dawn@4 359 if( n > length( outputValues ) )
Dawn@4 360 lenDiff = n - length( outputValues );
Dawn@4 361 outputValues = [ outputValues zeros( 1, lenDiff ) ];
Dawn@4 362 elseif( n < length( outputValues ) )
Dawn@4 363 lenDiff = length( outputValues ) - n;
Dawn@4 364 outputValues = [ outputValues zeros( 1, lenDiff ) ];
Dawn@4 365 end
Dawn@4 366
Dawn@4 367 data( fileCount, : ) = outputValues;
Dawn@4 368
Dawn@4 369 end
Dawn@4 370 lineCount = lineCount + 1;
Dawn@4 371
Dawn@4 372 end
Dawn@4 373 fclose(inputFileID);
Dawn@4 374
Dawn@4 375 % ------------ apply the k-means classifier ------------------------
Dawn@4 376
Dawn@4 377 noOfClusters = 2; % we are only trying to identify positive and negative emotions
Dawn@4 378
Dawn@4 379
Dawn@4 380 [idx ctrs]=kmeans( data, noOfClusters, 'Replicates',100,...
Dawn@4 381 'start', 'sample', 'Distance', 'cityblock');
Dawn@4 382
Dawn@4 383 %display results grouped by emotion
Dawn@4 384 fprintf( masterFileOutputID, '\n Emotion grouping \n');
Dawn@4 385 fprintf( masterFileOutputID, 'cityblock \n');
Dawn@4 386 [ groupStats, groupNames ] = processKMeansResults( 'cityblock', idx, sampleEmotion, masterFileOutputID, titleName, DEBUG );
Dawn@4 387 [ confusionMatrix ] = getConfusionMatrix( groupStats, groupNames, masterFileOutputID, 'cityblock' );
Dawn@4 388
Dawn@4 389
Dawn@4 390 fprintf( masterFileOutputID, 'sqEuclidean \n');
Dawn@4 391 [idx ctrs]=kmeans( data, noOfClusters, 'Replicates',100,...
Dawn@4 392 'start', 'sample', 'Distance', 'sqEuclidean');
Dawn@4 393
Dawn@4 394 [ groupStats, groupNames ] = processKMeansResults( 'sqEuclidean', idx, sampleEmotion, masterFileOutputID, titleName, DEBUG );
Dawn@4 395 [ confusionMatrix ] = getConfusionMatrix( groupStats, groupNames, masterFileOutputID, 'sqEuclidean' );
Dawn@4 396
Dawn@4 397
Dawn@4 398 fprintf( masterFileOutputID, 'cosine \n');
Dawn@4 399 [idx ctrs]=kmeans( data, noOfClusters, 'Replicates',100,...
Dawn@4 400 'start', 'sample', 'Distance', 'cosine');
Dawn@4 401
Dawn@4 402 [ groupStats, groupNames ] = processKMeansResults( 'cosine', idx, sampleEmotion, masterFileOutputID, titleName, DEBUG );
Dawn@4 403 [ confusionMatrix ] = getConfusionMatrix( groupStats, groupNames, masterFileOutputID,'cosine' );
Dawn@4 404
Dawn@4 405
Dawn@4 406 fprintf( masterFileOutputID, 'correlation \n');
Dawn@4 407 [idx ctrs]=kmeans( data, noOfClusters, 'Replicates',100,...
Dawn@4 408 'start', 'sample', 'Distance', 'correlation');
Dawn@4 409
Dawn@4 410 [ groupStats, groupNames ] = processKMeansResults( 'correlation', idx, sampleEmotion, masterFileOutputID, titleName, DEBUG );
Dawn@4 411 [ confusionMatrix ] = getConfusionMatrix( groupStats, groupNames, masterFileOutputID, 'correlation' );
Dawn@4 412
Dawn@4 413
Dawn@4 414 fprintf( masterFileOutputID, '\n' );
Dawn@4 415 fclose( masterFileOutputID );
Dawn@4 416
Dawn@4 417 end
Dawn@4 418
Dawn@4 419 %------------------------------------------------------------------
Dawn@4 420
Dawn@4 421 function [ outputValues ] = stripOutFormantValues( vars, outputValues )
Dawn@4 422
Dawn@4 423 noOfFormantValues = length( vars ) - 1; % gives the number of formant arguments only
Dawn@4 424 noOfFormants = vars(1);
Dawn@4 425 % there are 12 measurements for the mean of all formants (so the number
Dawn@4 426 % of formants is not important) for each formant measurement.
Dawn@4 427 if( noOfFormants ~= (noOfFormantValues-12)/24 )
Dawn@4 428 disp('EEK!');
Dawn@4 429 pause;
Dawn@4 430 else
Dawn@4 431 outputValues = [ outputValues vars( 2:end )' ];
Dawn@4 432 end
Dawn@4 433
Dawn@4 434 end
Dawn@4 435
Dawn@4 436 %-------------------------------------------------------------------