Changeset b9c3cd2


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Timestamp:
Nov 4, 2009, 11:52:00 PM (10 years ago)
Author:
Paul Brossier <piem@piem.org>
Branches:
feature/autosink, feature/constantq, feature/pitchshift, feature/pydocstrings, feature/timestretch, master, pitchshift, sampler, timestretch, yinfft+
Children:
998d4d6
Parents:
349e455
Message:

src/spectral/specdesc.h: add documentation about spectral shape descriptors

File:
1 edited

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  • src/spectral/specdesc.h

    r349e455 rb9c3cd2  
    2727  buffer and per channel (stored in a vector of size [channels]x[1]).
    2828 
    29   The following spectral description methods are available:
     29  A list of the spectral description methods currently available follows.
     30
     31  \section onsetdesc Onset detection functions
     32
     33  These functions are designed to raise at notes attacks in music signals.
    3034
    3135  \b \p energy : Energy based onset detection function
     
    7781  International Conference on Digital Audio Effects'' (DAFx-06), Montreal,
    7882  Canada, 2006.
    79  
     83
     84  \section shapedesc Spectral shape descriptors
     85
     86  The following descriptors are described in:
     87
     88  Geoffroy Peeters, <i>A large set of audio features for sound description
     89  (similarity and classification) in the CUIDADO project</i>, CUIDADO I.S.T.
     90  Project Report 2004 (<a
     91  href="http://www.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf">pdf</a>)
     92
     93  \b \p centroid : Spectral centroid
     94
     95  The spectral centroid represents the barycenter of the spectrum.
     96
     97  \e Note: This function returns the result in bin. To get the spectral
     98  centroid in Hz, aubio_bintofreq() should be used.
     99
     100  \b \p spread : Spectral spread
     101
     102  The spectral spread is the variance of the spectral distribution around its
     103  centroid.
     104
     105  See also <a href="http://en.wikipedia.org/wiki/Standard_deviation">Standard
     106  deviation</a> on Wikipedia.
     107
     108  \b \p skewness : Spectral skewness
     109
     110  Similarly, the skewness is computed from the third order moment of the
     111  spectrum. A negative skewness indicates more energy on the lower part of the
     112  spectrum. A positive skewness indicates more energy on the high frequency of
     113  the spectrum.
     114
     115  See also <a href="http://en.wikipedia.org/wiki/Skewness">Skewness</a> on
     116  Wikipedia.
     117
     118  \b \p kurtosis : Spectral kurtosis
     119
     120  The kurtosis is a measure of the flatness of the spectrum, computed from the
     121  fourth order moment.
     122
     123  See also <a href="http://en.wikipedia.org/wiki/Kurtosis">Kurtosis</a> on
     124  Wikipedia.
     125
     126  \b \p decrease : Spectral slope
     127
     128  The spectral slope represents decreasing rate of the spectral amplitude,
     129  computed using a linear regression.
     130
     131  \b \p decrease : Spectral decrease
     132
     133  The spectral decrease is another representation of the decreasing rate, 
     134  based on perceptual criteria.
     135
     136  \b \p rolloff : Spectral roll-off
     137
     138  This function returns the bin number below which 95% of the spectrum energy
     139  is found.
     140
    80141*/
    81142
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