1 | /* |
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2 | Copyright (C) 2003-2009 Paul Brossier <piem@aubio.org> |
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3 | |
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4 | This file is part of aubio. |
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5 | |
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6 | aubio is free software: you can redistribute it and/or modify |
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7 | it under the terms of the GNU General Public License as published by |
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8 | the Free Software Foundation, either version 3 of the License, or |
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9 | (at your option) any later version. |
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10 | |
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11 | aubio is distributed in the hope that it will be useful, |
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12 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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13 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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14 | GNU General Public License for more details. |
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15 | |
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16 | You should have received a copy of the GNU General Public License |
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17 | along with aubio. If not, see <http://www.gnu.org/licenses/>. |
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18 | |
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19 | */ |
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20 | |
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21 | /** \file |
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22 | |
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23 | Spectral description functions |
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24 | |
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25 | All of the following spectral description functions take as arguments the FFT |
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26 | of a windowed signal (as created with aubio_pvoc). They output one smpl_t per |
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27 | buffer and per channel (stored in a vector of size [channels]x[1]). |
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28 | |
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29 | A list of the spectral description methods currently available follows. |
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30 | |
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31 | \section onsetdesc Onset detection functions |
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32 | |
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33 | These functions are designed to raise at notes attacks in music signals. |
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34 | |
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35 | \b \p energy : Energy based onset detection function |
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36 | |
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37 | This function calculates the local energy of the input spectral frame. |
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38 | |
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39 | \b \p hfc : High Frequency Content onset detection function |
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40 | |
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41 | This method computes the High Frequency Content (HFC) of the input spectral |
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42 | frame. The resulting function is efficient at detecting percussive onsets. |
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43 | |
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44 | Paul Masri. Computer modeling of Sound for Transformation and Synthesis of |
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45 | Musical Signal. PhD dissertation, University of Bristol, UK, 1996. |
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46 | |
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47 | \b \p complex : Complex Domain Method onset detection function |
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48 | |
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49 | Christopher Duxbury, Mike E. Davies, and Mark B. Sandler. Complex domain |
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50 | onset detection for musical signals. In Proceedings of the Digital Audio |
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51 | Effects Conference, DAFx-03, pages 90-93, London, UK, 2003. |
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52 | |
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53 | \b \p phase : Phase Based Method onset detection function |
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54 | |
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55 | Juan-Pablo Bello, Mike P. Davies, and Mark B. Sandler. Phase-based note onset |
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56 | detection for music signals. In Proceedings of the IEEE International |
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57 | Conference on Acoustics Speech and Signal Processing, pages 441444, |
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58 | Hong-Kong, 2003. |
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59 | |
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60 | \b \p specdiff : Spectral difference method onset detection function |
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61 | |
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62 | Jonhatan Foote and Shingo Uchihashi. The beat spectrum: a new approach to |
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63 | rhythm analysis. In IEEE International Conference on Multimedia and Expo |
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64 | (ICME 2001), pages 881884, Tokyo, Japan, August 2001. |
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65 | |
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66 | \b \p kl : Kullback-Liebler onset detection function |
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67 | |
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68 | Stephen Hainsworth and Malcom Macleod. Onset detection in music audio |
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69 | signals. In Proceedings of the International Computer Music Conference |
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70 | (ICMC), Singapore, 2003. |
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71 | |
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72 | \b \p mkl : Modified Kullback-Liebler onset detection function |
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73 | |
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74 | Paul Brossier, ``Automatic annotation of musical audio for interactive |
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75 | systems'', Chapter 2, Temporal segmentation, PhD thesis, Centre for Digital |
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76 | music, Queen Mary University of London, London, UK, 2006. |
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77 | |
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78 | \b \p specflux : Spectral Flux |
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79 | |
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80 | Simon Dixon, Onset Detection Revisited, in ``Proceedings of the 9th |
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81 | International Conference on Digital Audio Effects'' (DAFx-06), Montreal, |
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82 | Canada, 2006. |
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83 | |
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84 | \section shapedesc Spectral shape descriptors |
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85 | |
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86 | The following descriptors are described in: |
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87 | |
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88 | Geoffroy Peeters, <i>A large set of audio features for sound description |
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89 | (similarity and classification) in the CUIDADO project</i>, CUIDADO I.S.T. |
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90 | Project Report 2004 (<a |
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91 | href="http://www.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf">pdf</a>) |
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92 | |
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93 | \b \p centroid : Spectral centroid |
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94 | |
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95 | The spectral centroid represents the barycenter of the spectrum. |
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96 | |
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97 | \e Note: This function returns the result in bin. To get the spectral |
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98 | centroid in Hz, aubio_bintofreq() should be used. |
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99 | |
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100 | \b \p spread : Spectral spread |
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101 | |
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102 | The spectral spread is the variance of the spectral distribution around its |
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103 | centroid. |
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104 | |
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105 | See also <a href="http://en.wikipedia.org/wiki/Standard_deviation">Standard |
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106 | deviation</a> on Wikipedia. |
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107 | |
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108 | \b \p skewness : Spectral skewness |
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109 | |
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110 | Similarly, the skewness is computed from the third order moment of the |
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111 | spectrum. A negative skewness indicates more energy on the lower part of the |
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112 | spectrum. A positive skewness indicates more energy on the high frequency of |
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113 | the spectrum. |
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114 | |
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115 | See also <a href="http://en.wikipedia.org/wiki/Skewness">Skewness</a> on |
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116 | Wikipedia. |
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117 | |
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118 | \b \p kurtosis : Spectral kurtosis |
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119 | |
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120 | The kurtosis is a measure of the flatness of the spectrum, computed from the |
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121 | fourth order moment. |
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122 | |
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123 | See also <a href="http://en.wikipedia.org/wiki/Kurtosis">Kurtosis</a> on |
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124 | Wikipedia. |
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125 | |
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126 | \b \p decrease : Spectral slope |
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127 | |
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128 | The spectral slope represents decreasing rate of the spectral amplitude, |
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129 | computed using a linear regression. |
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130 | |
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131 | \b \p decrease : Spectral decrease |
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132 | |
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133 | The spectral decrease is another representation of the decreasing rate, |
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134 | based on perceptual criteria. |
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135 | |
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136 | \b \p rolloff : Spectral roll-off |
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137 | |
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138 | This function returns the bin number below which 95% of the spectrum energy |
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139 | is found. |
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140 | |
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141 | */ |
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142 | |
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143 | |
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144 | #ifndef ONSETDETECTION_H |
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145 | #define ONSETDETECTION_H |
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146 | |
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147 | #ifdef __cplusplus |
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148 | extern "C" { |
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149 | #endif |
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150 | |
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151 | /** spectral description structure */ |
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152 | typedef struct _aubio_specdesc_t aubio_specdesc_t; |
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153 | |
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154 | /** execute spectral description function on a spectral frame |
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155 | |
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156 | Generic function to compute spectral detescription. |
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157 | |
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158 | \param o spectral description object as returned by new_aubio_specdesc() |
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159 | \param fftgrain input signal spectrum as computed by aubio_pvoc_do |
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160 | \param desc output vector (one sample long, to send to the peak picking) |
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161 | |
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162 | */ |
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163 | void aubio_specdesc_do (aubio_specdesc_t * o, cvec_t * fftgrain, |
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164 | fvec_t * desc); |
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165 | |
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166 | /** creation of a spectral description object |
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167 | |
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168 | \param method spectral description method |
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169 | \param buf_size length of the input spectrum frame |
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170 | \param channels number of input channels |
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171 | |
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172 | */ |
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173 | aubio_specdesc_t *new_aubio_specdesc (char_t * method, uint_t buf_size, |
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174 | uint_t channels); |
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175 | |
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176 | /** deletion of a spectral descriptor |
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177 | |
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178 | \param o spectral descriptor object as returned by new_aubio_specdesc() |
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179 | |
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180 | */ |
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181 | void del_aubio_specdesc (aubio_specdesc_t * o); |
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182 | |
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183 | #ifdef __cplusplus |
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184 | } |
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185 | #endif |
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186 | |
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187 | #endif /* ONSETDETECTION_H */ |
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