[96fb8ad] | 1 | /* |
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[e6a78ea] | 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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[96fb8ad] | 19 | */ |
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| 20 | |
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[6ebcb08] | 21 | /** \file |
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| 22 | |
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[bf2e7a7] | 23 | Spectral description functions |
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[6ebcb08] | 24 | |
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[bf2e7a7] | 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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[6ebcb08] | 27 | buffer and per channel (stored in a vector of size [channels]x[1]). |
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| 28 | |
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[b9c3cd2] | 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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[6ebcb08] | 34 | |
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[bf2e7a7] | 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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[b9c3cd2] | 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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[6ebcb08] | 141 | */ |
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[96fb8ad] | 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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[bf2e7a7] | 151 | /** spectral description structure */ |
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[31907fd] | 152 | typedef struct _aubio_specdesc_t aubio_specdesc_t; |
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[6ebcb08] | 153 | |
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[bf2e7a7] | 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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[6ebcb08] | 157 | |
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[bf2e7a7] | 158 | \param o spectral description object as returned by new_aubio_specdesc() |
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[6ebcb08] | 159 | \param fftgrain input signal spectrum as computed by aubio_pvoc_do |
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[bf2e7a7] | 160 | \param desc output vector (one sample long, to send to the peak picking) |
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[6ebcb08] | 161 | |
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| 162 | */ |
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[bf2e7a7] | 163 | void aubio_specdesc_do (aubio_specdesc_t * o, cvec_t * fftgrain, |
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| 164 | fvec_t * desc); |
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[6ebcb08] | 165 | |
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[bf2e7a7] | 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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[6ebcb08] | 170 | \param channels number of input channels |
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| 171 | |
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| 172 | */ |
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[bf2e7a7] | 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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[6ebcb08] | 177 | |
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[bf2e7a7] | 178 | \param o spectral descriptor object as returned by new_aubio_specdesc() |
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[6ebcb08] | 179 | |
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| 180 | */ |
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[bf2e7a7] | 181 | void del_aubio_specdesc (aubio_specdesc_t * o); |
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[e9d8cfe] | 182 | |
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[96fb8ad] | 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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