ref: 9906b3f3f22649481dc60d3bcefedea5440225b3
dir: /src/spectral/specdesc.h/
/*
Copyright (C) 2003-2009 Paul Brossier <piem@aubio.org>
This file is part of aubio.
aubio is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
aubio is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with aubio. If not, see <http://www.gnu.org/licenses/>.
*/
/** \file
Spectral description functions
All of the following spectral description functions take as arguments the FFT
of a windowed signal (as created with aubio_pvoc). They output one smpl_t per
buffer (stored in a vector of size [1]).
A list of the spectral description methods currently available follows.
\section onsetdesc Onset detection functions
These functions are designed to raise at notes attacks in music signals.
\b \p energy : Energy based onset detection function
This function calculates the local energy of the input spectral frame.
\b \p hfc : High Frequency Content onset detection function
This method computes the High Frequency Content (HFC) of the input spectral
frame. The resulting function is efficient at detecting percussive onsets.
Paul Masri. Computer modeling of Sound for Transformation and Synthesis of
Musical Signal. PhD dissertation, University of Bristol, UK, 1996.
\b \p complex : Complex Domain Method onset detection function
Christopher Duxbury, Mike E. Davies, and Mark B. Sandler. Complex domain
onset detection for musical signals. In Proceedings of the Digital Audio
Effects Conference, DAFx-03, pages 90-93, London, UK, 2003.
\b \p phase : Phase Based Method onset detection function
Juan-Pablo Bello, Mike P. Davies, and Mark B. Sandler. Phase-based note onset
detection for music signals. In Proceedings of the IEEE International
Conference on Acoustics Speech and Signal Processing, pages 441444,
Hong-Kong, 2003.
\b \p specdiff : Spectral difference method onset detection function
Jonhatan Foote and Shingo Uchihashi. The beat spectrum: a new approach to
rhythm analysis. In IEEE International Conference on Multimedia and Expo
(ICME 2001), pages 881884, Tokyo, Japan, August 2001.
\b \p kl : Kullback-Liebler onset detection function
Stephen Hainsworth and Malcom Macleod. Onset detection in music audio
signals. In Proceedings of the International Computer Music Conference
(ICMC), Singapore, 2003.
\b \p mkl : Modified Kullback-Liebler onset detection function
Paul Brossier, ``Automatic annotation of musical audio for interactive
systems'', Chapter 2, Temporal segmentation, PhD thesis, Centre for Digital
music, Queen Mary University of London, London, UK, 2006.
\b \p specflux : Spectral Flux
Simon Dixon, Onset Detection Revisited, in ``Proceedings of the 9th
International Conference on Digital Audio Effects'' (DAFx-06), Montreal,
Canada, 2006.
\section shapedesc Spectral shape descriptors
The following descriptors are described in:
Geoffroy Peeters, <i>A large set of audio features for sound description
(similarity and classification) in the CUIDADO project</i>, CUIDADO I.S.T.
Project Report 2004 (<a
href="http://www.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf">pdf</a>)
\b \p centroid : Spectral centroid
The spectral centroid represents the barycenter of the spectrum.
\e Note: This function returns the result in bin. To get the spectral
centroid in Hz, aubio_bintofreq() should be used.
\b \p spread : Spectral spread
The spectral spread is the variance of the spectral distribution around its
centroid.
See also <a href="http://en.wikipedia.org/wiki/Standard_deviation">Standard
deviation</a> on Wikipedia.
\b \p skewness : Spectral skewness
Similarly, the skewness is computed from the third order moment of the
spectrum. A negative skewness indicates more energy on the lower part of the
spectrum. A positive skewness indicates more energy on the high frequency of
the spectrum.
See also <a href="http://en.wikipedia.org/wiki/Skewness">Skewness</a> on
Wikipedia.
\b \p kurtosis : Spectral kurtosis
The kurtosis is a measure of the flatness of the spectrum, computed from the
fourth order moment.
See also <a href="http://en.wikipedia.org/wiki/Kurtosis">Kurtosis</a> on
Wikipedia.
\b \p slope : Spectral slope
The spectral slope represents decreasing rate of the spectral amplitude,
computed using a linear regression.
\b \p decrease : Spectral decrease
The spectral decrease is another representation of the decreasing rate,
based on perceptual criteria.
\b \p rolloff : Spectral roll-off
This function returns the bin number below which 95% of the spectrum energy
is found.
*/
#ifndef ONSETDETECTION_H
#define ONSETDETECTION_H
#ifdef __cplusplus
extern "C" {
#endif
/** spectral description structure */
typedef struct _aubio_specdesc_t aubio_specdesc_t;
/** execute spectral description function on a spectral frame
Generic function to compute spectral detescription.
\param o spectral description object as returned by new_aubio_specdesc()
\param fftgrain input signal spectrum as computed by aubio_pvoc_do
\param desc output vector (one sample long, to send to the peak picking)
*/
void aubio_specdesc_do (aubio_specdesc_t * o, cvec_t * fftgrain,
fvec_t * desc);
/** creation of a spectral description object
\param method spectral description method
\param buf_size length of the input spectrum frame
*/
aubio_specdesc_t *new_aubio_specdesc (char_t * method, uint_t buf_size);
/** deletion of a spectral descriptor
\param o spectral descriptor object as returned by new_aubio_specdesc()
*/
void del_aubio_specdesc (aubio_specdesc_t * o);
#ifdef __cplusplus
}
#endif
#endif /* ONSETDETECTION_H */