Creating [resonators~] tuplets using fluid.bufsinefeature~?

First off, all the sines objects totally slipped under my radar as they came out after I was actively playing/exploring things, but for some upcoming SP-Tools updates, I’ve been messing with CNMAT’s resonators~ and just doing pure sinusoidal resynthesis roughly based on the Resonator device from confetti (which was based around sigmund~, since it offered multiple peak outputs). Obviously can totally get that now from fluid.bufsinefeature~/fluid.sinefeature~ which is fantastic!

So other than wrestling with resonators~ (wanting to do the same functionality natively, for reducing dependencies, but also it seems to be super buggy, leading to loads of instacrashes), I was thinking that it would be great to create some new models for it.

There’s an IRCAM patch for this (MaxModRes), but I can’t make heads or tails of it, and it seems like overkill for what I’m after.

So the tuplet format that resonators~ wants is frequency, gain, and “decayrate” variables for each filter. I can presumably use the frequency/gain outputs from fluid.bufsinefeature~fluid.bufstats~ @select mean to give me the frequencies and gains, but the decayrate is a bit more complicated. I would think that the derivative of loudness would be handy for this, but I wouldn’t know how to translate that into “decayrate”. I had a look at the resonators~.c file (github), but it’s pretty impenetrable to me, so I have no idea what the “decayrate” is actually doing. I’m guessing it’s some kind of dB over time value or something like that, but in what units? How to compute it? etc…

So yeah, any thoughts on how to generate frequency, gain, and decayrate tuplets in the fluid.verse~?

Yes, they’re not quite the same thing, which is why it’s not immediately obvious how to get from one to the other.

If fluid.bufsinefeature was doing partial tracking rather than just peak tracking, it would be a bit easier, because then you’ve got some groupings against which to try and estimate a degree of noisiness (perhaps using the standard deviation of the frequencies in a track), which the CNAMT res-transform object suggests (slightly obliquely). Unfortunately, I don’t know of anything that only does partial tracking on a list of freq / mag peaks, either real-time or on buffers.

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It is still on my radar to try to extract the voice allocation from sines into an object… I’ll let you know if I get anywhere.

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For resontators~, decayrate is inversely related to the Q of the filter. Sharper filters ring longer, so have a lower decayrate. It use to be possible to generate resonant models using IRCAM’s ResAn, but that’s long gone. (Although, I think the source is somewhere.)

There are a collection of more-or-less scientific ways to generate decayrates. There’s a patch called sin-to-res.maxpat in the CNMAT mmj depot that does some of them. It’s in here: CNMAT-MMJ-Depot/patchers/synthesis at master · CNMAT/CNMAT-MMJ-Depot · GitHub I thought there was another one by Daniel Cullen, but I can’t find it quickly.

The truth is that some pretty simplistic approaches to generating decay rate work pretty well. Most acoustic sounds will have higher decayrates as the frequency goes up. Lower partials ring longer. YMMV

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Ok managed to push this a bit further and got something working ok.

Inharmonic metal stuff is quite problematic for this (as one can imagine) but I found I got much better results when only analyzing the first half of when splitting via time centroid (a FluCoMa-based solution @a.harker helped me with a while back). My initial thinking was that the derivative (of loudness) would be dogshit for a long/sustained sample as at some point it becomes quite flat in decay and that would overly impact the statistical summary. But I found that it also improves the peak tracking too, which makes since since the (perceptual) peaks would be more present in that part of the sound file anyways.

Still not optimized the resonator~-esque playback (using an mc.reson~ hack at the moment), but it’s somewhat ok in terms of the overall duration/decay, based on the derivative of loudness.


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Here are a couple test sound files too. With works well.wav you can really hear the difference analyzing only the first (via time centroid) makes. For the other two there are weird quirks I can’t make sense of. The problematic.wav one I think is just an inharmonic/perceptual thing (though even that seems weird) and detunes?.wav confuses me. It sounds like it’s a bin off or something when going between full/half analysis, but that doesn’t make sense as the fft settings stay consistent.

But yeah, pretty promising results so far!

audioexamples.zip (466.9 KB)

Actually listening to the examples (attached) again, problematic.wav seems even weirder. When analyzing the whole file it has that ‘off by a bin’ sound where it sounds a halftone flat. But when analyzing the time centroid first half it’s pretty solidly detuned by a tritone. Is there some weird frequency/fft/peak phenomena that I’m overlooking here?