fractional-octave frequency smoothing

    Mar 27 2006 | 8:30 pm
    Hi list;
    I have some audio fft data stored as jitter matrices, and would like to be able to smooth it to some arbitrary bandwidth, e.g. 1/3rd octave or whatever.
    So I suppose I need to either use a smoothing kernel that gets wider as I move from low to high frequency, or perhaps first convert to a log frequency representation, and then do the smoothing?
    I'd be very interested to hear of anyone doing such things in jitter.
    Best, Eamonn

    • Mar 29 2006 | 11:50 pm
      Hi Eamonn,
      When you say "smooth it", I am assuming you mean transform the data somehow into 1.3 octave representations rather than the FFTs linear frequency distribution... correct? I think using a kernel with variable width should give the same results as converting to a log frequency representation and using a kernel of fixed width.
      The linearity of freq bins is one of the big weaknesses of the FFT. Wavelet transforms are promising in this regard. A while ago I completed some preliminary work to make this technology available in Max, but I haven't finished the project. I'm hoping it will be included in a future version of the jitter.
    • Mar 30 2006 | 6:34 pm
      On 30-Mar-2006, at 1:50, Ben Nevile wrote: > The linearity of freq bins is one of the big weaknesses of the FFT.
      Coming a little late to this thread, but I recall now that I worked around this "weakness" by grouping FFT bins into (approx.) 1/3rd octave groups and handling the groups as a unit. It worked fairly well in my Spectral Mutation object, lp.frim~.
      Credit where credit is due: I got the idea from talking with Tom Erbe and Larry Polansky, chatting about our various implementations of mutation algorithms.
      The algorithm I used for grouping bins might be more procedural- language friendly than Max-friendly, but I suppose it could be done with patch cords. FTR, lp.frim~ supports octave division from one to fifteen "virtual bins" per octave (as well as plain vanilla FFT linear bins).
      -- Peter
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