[PD] feature extraction

[Jacob Last]

Hi Jamie-

Thanks, I would love to see the abstractions, as I was sort of
shooting in the dark for a while implementing even the relatively
simple spectral centroid. I originally thought I should be able to do
the computation all in the signal domain from the [rfft~] object's
outputs....is that possible? What I ended up doing is writing each
analysis frame into an array, then using [bang~] to trigger the
calculation for each frame, reading through the array.

Well, if you could package those up it would be immensely appreciated!

Jacob

On 7/15/05, Jamie Bullock <jamie at postlude.co.uk> wrote:
> 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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