[PD] feature extraction

[Jamie Bullock]

Hi Jacob,

A lot of work has been done on this, particularly in the field of MIR
(Musical Information Retrival). One method is to treat the frequency
spectrum as a statistical distribution, and then extract various
characteristics of the distribution. These can include:

Mean: the arithmetic average
Variance: the spectral 'spread' about the mean
Deviaton: the square root of the variance
Skewness: a measure of asymmetry around the mean
Kurtosis: A measure of the relative spectral peakedness
Irregularity: A measure of the jaggedness of the spectrum

There are many others including Tristimulus and Inharmonicity, but I
can't remember the definitions off-hand. A Google for any of the above
should give you the formulae.

I have a set of abstractions that implement some of the above. I'll
package them up and make them available within the next couple of days. 

Regards,

Jamie






On Fri, 2005-07-15 at 10:44 -0400, Jacob Last wrote:
> Hi all--
> 
> I'm currently working on a project for controlling my granular synth
> patch using a control stream derived from various feature extractions
> from an input signal (soundfile or live). Currently what I'm working
> with is the spectral centroid, which I've implemented as a PD patch.
> 
> I'm wonding if people have other ideas for perceptual features that
> can be reliably extracted from an audio stream using the FFT or
> otherwise. The input is not necessarily pitched (might eventually want
> to analyze its own granular output as well, in addition to noisy and
> unpitched sounds) so I'm not that interested in pitch tracking, etc.
> rather more high level sonic features. For example, how might I detect
> a period of sharp attacks on a wind instrument? Maybe by using some
> sort of peak threshold with the spectral centroid? "Smoothness" of a
> sound?  Continuum of pitched to unpitched? Etc.
> 
> Also if there are any PD implementations (abstractions or externals)
> of this sort of stuff please inform me; I haven't found anything as of
> yet.
> 
> I'd very much appreciate any input!
> 
> Best,
> Jacob
> 
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