source: src/spectral/specdesc.h @ c23e591

feature/autosinkfeature/cnnfeature/cnn_orgfeature/constantqfeature/crepefeature/crepe_orgfeature/pitchshiftfeature/pydocstringsfeature/timestretchfix/ffmpeg5sampler
Last change on this file since c23e591 was c23e591, checked in by Paul Brossier <piem@piem.org>, 7 years ago

src/spectral/specdesc.c: add weighted phase deviation

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1/*
2  Copyright (C) 2003-2013 Paul Brossier <piem@aubio.org>
3
4  This file is part of aubio.
5
6  aubio is free software: you can redistribute it and/or modify
7  it under the terms of the GNU General Public License as published by
8  the Free Software Foundation, either version 3 of the License, or
9  (at your option) any later version.
10
11  aubio is distributed in the hope that it will be useful,
12  but WITHOUT ANY WARRANTY; without even the implied warranty of
13  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
14  GNU General Public License for more details.
15
16  You should have received a copy of the GNU General Public License
17  along with aubio.  If not, see <http://www.gnu.org/licenses/>.
18
19*/
20
21/** \file
22
23  Spectral description functions
24
25  All of the following spectral description functions take as arguments the FFT
26  of a windowed signal (as created with aubio_pvoc). They output one smpl_t per
27  buffer (stored in a vector of size [1]).
28
29  \section specdesc Spectral description functions
30
31  A list of the spectral description methods currently available follows.
32
33  \subsection onsetdesc Onset detection functions
34
35  These functions are designed to raise at notes attacks in music signals.
36
37  \b \p energy : Energy based onset detection function
38
39  This function calculates the local energy of the input spectral frame.
40
41  \b \p hfc : High Frequency Content onset detection function
42
43  This method computes the High Frequency Content (HFC) of the input spectral
44  frame. The resulting function is efficient at detecting percussive onsets.
45
46  Paul Masri. Computer modeling of Sound for Transformation and Synthesis of
47  Musical Signal. PhD dissertation, University of Bristol, UK, 1996.
48
49  \b \p complex : Complex Domain Method onset detection function
50
51  Christopher Duxbury, Mike E. Davies, and Mark B. Sandler. Complex domain
52  onset detection for musical signals. In Proceedings of the Digital Audio
53  Effects Conference, DAFx-03, pages 90-93, London, UK, 2003.
54
55  \b \p phase : Phase Based Method onset detection function
56
57  Juan-Pablo Bello, Mike P. Davies, and Mark B. Sandler. Phase-based note onset
58  detection for music signals. In Proceedings of the IEEE International
59  Conference on Acoustics Speech and Signal Processing, pages 441­444,
60  Hong-Kong, 2003.
61
62  \b \p wphase : Weighted Phase Deviation onset detection function
63
64  S. Dixon. Onset detection revisited. In Proceedings of the 9th International
65  Conference on Digital Audio Ef- fects (DAFx) , pages 133–137, 2006.
66
67  http://www.eecs.qmul.ac.uk/~simond/pub/2006/dafx.pdf
68
69  \b \p specdiff : Spectral difference method onset detection function
70
71  Jonhatan Foote and Shingo Uchihashi. The beat spectrum: a new approach to
72  rhythm analysis. In IEEE International Conference on Multimedia and Expo
73  (ICME 2001), pages 881­884, Tokyo, Japan, August 2001.
74
75  \b \p kl : Kullback-Liebler onset detection function
76
77  Stephen Hainsworth and Malcom Macleod. Onset detection in music audio
78  signals. In Proceedings of the International Computer Music Conference
79  (ICMC), Singapore, 2003.
80
81  \b \p mkl : Modified Kullback-Liebler onset detection function
82
83  Paul Brossier, ``Automatic annotation of musical audio for interactive
84  systems'', Chapter 2, Temporal segmentation, PhD thesis, Centre for Digital
85  music, Queen Mary University of London, London, UK, 2006.
86
87  \b \p specflux : Spectral Flux
88
89  Simon Dixon, Onset Detection Revisited, in ``Proceedings of the 9th
90  International Conference on Digital Audio Effects'' (DAFx-06), Montreal,
91  Canada, 2006.
92
93  \subsection shapedesc Spectral shape descriptors
94
95  The following descriptors are described in:
96
97  Geoffroy Peeters, <i>A large set of audio features for sound description
98  (similarity and classification) in the CUIDADO project</i>, CUIDADO I.S.T.
99  Project Report 2004 (<a
100  href="http://www.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf">pdf</a>)
101
102  \b \p centroid : Spectral centroid
103
104  The spectral centroid represents the barycenter of the spectrum.
105
106  \e Note: This function returns the result in bin. To get the spectral
107  centroid in Hz, aubio_bintofreq() should be used.
108
109  \b \p spread : Spectral spread
110
111  The spectral spread is the variance of the spectral distribution around its
112  centroid.
113
114  See also <a href="http://en.wikipedia.org/wiki/Standard_deviation">Standard
115  deviation</a> on Wikipedia.
116
117  \b \p skewness : Spectral skewness
118
119  Similarly, the skewness is computed from the third order moment of the
120  spectrum. A negative skewness indicates more energy on the lower part of the
121  spectrum. A positive skewness indicates more energy on the high frequency of
122  the spectrum.
123
124  See also <a href="http://en.wikipedia.org/wiki/Skewness">Skewness</a> on
125  Wikipedia.
126
127  \b \p kurtosis : Spectral kurtosis
128
129  The kurtosis is a measure of the flatness of the spectrum, computed from the
130  fourth order moment.
131
132  See also <a href="http://en.wikipedia.org/wiki/Kurtosis">Kurtosis</a> on
133  Wikipedia.
134
135  \b \p slope : Spectral slope
136
137  The spectral slope represents decreasing rate of the spectral amplitude,
138  computed using a linear regression.
139
140  \b \p decrease : Spectral decrease
141
142  The spectral decrease is another representation of the decreasing rate,
143  based on perceptual criteria.
144
145  \b \p rolloff : Spectral roll-off
146
147  This function returns the bin number below which 95% of the spectrum energy
148  is found.
149
150  \example spectral/test-specdesc.c
151
152*/
153
154
155#ifndef AUBIO_SPECDESC_H
156#define AUBIO_SPECDESC_H
157
158#ifdef __cplusplus
159extern "C" {
160#endif
161
162/** spectral description structure */
163typedef struct _aubio_specdesc_t aubio_specdesc_t;
164
165/** execute spectral description function on a spectral frame
166
167  Generic function to compute spectral description.
168
169  \param o spectral description object as returned by new_aubio_specdesc()
170  \param fftgrain input signal spectrum as computed by aubio_pvoc_do
171  \param desc output vector (one sample long, to send to the peak picking)
172
173*/
174void aubio_specdesc_do (aubio_specdesc_t * o, const cvec_t * fftgrain,
175    fvec_t * desc);
176
177/** creation of a spectral description object
178
179  \param method spectral description method
180  \param buf_size length of the input spectrum frame
181
182  The parameter \p method is a string that can be any of:
183
184    - `energy`, `hfc`, `complex`, `phase`, `specdiff`, `kl`, `mkl`, `specflux`
185    - `centroid`, `spread`, `skewness`, `kurtosis`, `slope`, `decrease`, `rolloff`
186
187*/
188aubio_specdesc_t *new_aubio_specdesc (const char_t * method, uint_t buf_size);
189
190/** deletion of a spectral descriptor
191
192  \param o spectral descriptor object as returned by new_aubio_specdesc()
193
194*/
195void del_aubio_specdesc (aubio_specdesc_t * o);
196
197#ifdef __cplusplus
198}
199#endif
200
201#endif /* AUBIO_SPECDESC_H */
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