aubio
0.4.9

Spectral description functions. More...
Go to the source code of this file.
Typedefs  
typedef struct _aubio_specdesc_t  aubio_specdesc_t 
spectral description structure  
Functions  
void  aubio_specdesc_do (aubio_specdesc_t *o, const cvec_t *fftgrain, fvec_t *desc) 
execute spectral description function on a spectral frame More...  
aubio_specdesc_t *  new_aubio_specdesc (const char_t *method, uint_t buf_size) 
creation of a spectral description object More...  
void  del_aubio_specdesc (aubio_specdesc_t *o) 
deletion of a spectral descriptor More...  
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.
These functions are designed to raise at notes attacks in music signals.
energy
: Energy based onset detection function
This function calculates the local energy of the input spectral frame.
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.
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, DAFx03, pages 9093, London, UK, 2003.
phase
: Phase Based Method onset detection function
JuanPablo Bello, Mike P. Davies, and Mark B. Sandler. Phasebased note onset detection for music signals. In Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing, pages 441444, HongKong, 2003.
wphase
: Weighted Phase Deviation onset detection function
S. Dixon. Onset detection revisited. In Proceedings of the 9th International Conference on Digital Audio Ef fects (DAFx) , pages 133–137, 2006.
http://www.eecs.qmul.ac.uk/~simond/pub/2006/dafx.pdf
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.
kl
: KullbackLiebler 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.
mkl
: Modified KullbackLiebler 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.
specflux
: Spectral Flux
Simon Dixon, Onset Detection Revisited, in ``Proceedings of the 9th International Conference on Digital Audio Effects'' (DAFx06), Montreal, Canada, 2006.
The following descriptors are described in:
Geoffroy Peeters, A large set of audio features for sound description (similarity and classification) in the CUIDADO project, CUIDADO I.S.T. Project Report 2004 (pdf)
centroid
: Spectral centroid
The spectral centroid represents the barycenter of the spectrum.
Note: This function returns the result in bin. To get the spectral centroid in Hz, aubio_bintofreq() should be used.
spread
: Spectral spread
The spectral spread is the variance of the spectral distribution around its centroid.
See also Standard deviation on Wikipedia.
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 Skewness on Wikipedia.
kurtosis
: Spectral kurtosis
The kurtosis is a measure of the flatness of the spectrum, computed from the fourth order moment.
See also Kurtosis on Wikipedia.
slope
: Spectral slope
The spectral slope represents decreasing rate of the spectral amplitude, computed using a linear regression.
decrease
: Spectral decrease
The spectral decrease is another representation of the decreasing rate, based on perceptual criteria.
rolloff
: Spectral rolloff
This function returns the bin number below which 95% of the spectrum energy is found.
Definition in file specdesc.h.
void aubio_specdesc_do  (  aubio_specdesc_t *  o, 
const cvec_t *  fftgrain,  
fvec_t *  desc  
) 
execute spectral description function on a spectral frame
Generic function to compute spectral description.
o  spectral description object as returned by new_aubio_specdesc() 
fftgrain  input signal spectrum as computed by aubio_pvoc_do 
desc  output vector (one sample long, to send to the peak picking) 
void del_aubio_specdesc  (  aubio_specdesc_t *  o  ) 
deletion of a spectral descriptor
o  spectral descriptor object as returned by new_aubio_specdesc() 
aubio_specdesc_t* new_aubio_specdesc  (  const char_t *  method, 
uint_t  buf_size  
) 
creation of a spectral description object
method  spectral description method 
buf_size  length of the input spectrum frame 
The parameter method
is a string that can be any of:
complex
, energy
, hfc
, kl
, mkl
, phase
, specdiff
, specflux
, wphase
,centroid
, decrease
, kurtosis
, rolloff
, skewness
, slope
, spread
.