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#183686
brock
Participant

    … what Brock said!

    Tony, I’ve been giving that some deep thought (of course).  Some upsides of SCALA for H90 end users:

    • As little as a dozen or so short lines of .txt in any standard editor.
    • Go as simple or as complex as you want.  Easy to get started.
    • Huge potential to create any kind of scale overlay, and even performance tools.
    • Free, deep & often updated core application.
    • Tiny files, with minimal space required to store many, many tuning templates.
    • Historically accurate period tunings {yawn!}
    • The aforementioned per-note (de)tuning.

    Then I thought about the possible  logistics & ROI on ET’s end:

    • Would you first need to SIFT a pitch (or pitches), shift intelligently, extrapolate MIDI Notes, process all that with a select Scala file, then reverse the l translation process back to pitches again?  I really don’t know, but I’m guessing there’s a potential latency generator.
    • Using static Pitchbend messages would be at least as processor-intensive.  And there’s not any demand for PB support in general for the H90 (unlike the H9), so it would seem to be not worth pursuing.

    Back to per-note detuning.  It’s an amazing effect on synths (and easier to implement, I suppose).  You can approach this on the H90 with some kind of pseudo-random external control.  Be that expression pedal, 8 Step, MIDI, maybe even 3 HotSwitches + 3 / 6 Aux switches.  Even better if tied to an envelope follower for per-note triggers.

    So, load up MicroPitch, H910 H949 or similar, and map your “random” controller to the Pitch parameters, in different ranges.  Load up a 2nd algo, and do the same.

    Same concept with other algos featuring Detune parameters.  Or simplify all that and use ENV controls instead.)  A little detuned depth goes a long way with stacked instances of it.  Maintain a fairly even dry/wet Mix overall.

    Not exactly a “per-note” template, but very similar results.  The semi-random  depth of detuning create the variable beating and perceived rate changes.

    Come to think of it: just combine both of your requests into one algorithm.  That LFO is essential.  Maybe – just maybe – I will find my Holy Grail inside: the “perfect” doubler effect.