[PD] feature extraction

[Jamie Bullock]

Hi,

I was trying to achieve something slightly different to you in that I
needed to do a periodic 'snapshot' of the features rather than generate
continuous feature curves. I actually used the spectral peak data
generated by fiddle~ as the basis for the calculations. As such, I was
only dealing with 'control data'. I think for your purposes, Mathieu's
suggestions sound good. Anyhow, you might get some use from my
abstractions, so I have posted them at:
http://www.puredata.org/Members/jb

I used them for rapid testing of a timbre classification technique so
they are very rough. You may even spot some faults! At some point soon,
I might put together an external that does the job more elegantly. Let
me know how you get on.

Regards,

Jamie



On Fri, 2005-07-15 at 12:28 -0400, Jacob Last wrote:
> 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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> > 
> >
> 
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