Sinusoidal & Stochastic/noise decomposition

Hi all,

I wonder if anyone has an implementation for this? I'd need partial extraction similar to sigmund~ but I would love to get the synthesized sound to be as close to the original as possible.

Xavier Serra's dissertation (http://mtg.upf.edu/files/publications/PhD-Thesis-1989-xserra.pdf) does partial tracking and synthesis and then subtracts that signal from the original in the frequency domain. If the phase is preserved it can be subtracted in the time domain.

If I have to implement this myself I would probably use sigmund~ and do the subtraction inside a pfft~ patch. I know that in Serra's paper he smooths out the noise as a smooth frequency contour so the general shape of the stochastic part is preserved and made more conducive to transformation through a simpler representation. I will probably try this out but maybe someone has a better implementation already made?

I'm only using this so that I can highlight partials and do time streching with the oscillator control data sigmund~ gives but to add a little realism to the signal.
It would also be nice to somehow avoid all the craziness sigmund~ produces during more turbulent parts of the signal (attacks), perhaps changing the noise/sinusoidal mix depending on amplitude fluctuations and zero crossing rate(noisiness)?

Any thoughts are much appreciated. I'm not wedded to using sigmund~ but something that'll give me control data for a collection of oscillators would be ideal while giving me the residual.

My final question is, how about that phase information on the sinusoidal part? Although I know it doesn't matter perceptually, I would like a way of preserving this because of my project's technical needs (I'm too much of a noob to implement partial tracking myself).