EQ curve from object.

[d.healey]

@Christoph-Hart Because I'm a noob :) can I load in curves from external analysis into a scriptnode filter?

[Christoph Hart]

@d-healey Sure, it's called scriptnode for a reason. You can grab references to every node and set the parameter programatically.

[d.healey]

@Christoph-Hart I have some learning to do :)

[Dan Korneff]

@d-healey Can't wait for the Patreon video

[Christoph Hart]

@Dan-Korneff Everybody is waiting for this video and I really don't know why it takes so long for this guy to learn scriptnode :)

[d.healey]

I can't see a node that is like the EQ, are you suggesting I add individual filters for every band? Is this more/less efficient than the using the stock EQ?

[Dan Korneff]

@d-healey I believe it's only 1 band per node.

[d.healey]

@Dan-Korneff And if I wanted to add 30 or so bands, any idea how the efficiency would compare to the EQ effect? And how would it compare to just adding 30 filter effects?

[Matt_SF]

@d-healey I can be wrong but : Talking only about using 30 1-band EQ nodes, I would guess that once your ScriptFX is compiled into a HardcodedFX, there won't be much of a difference than using an EQ module with 30 bands.

[Christoph Hart]

Yes it‘s pretty much the same.

[d.healey]

Excellent. Is the clone control node thing working properly?

[Christoph Hart]

@d-healey A simple test for your use case works, but the entire concept is a little unstable (it's basically the child panels of scriptnode) so I'm not sure I would recommend it at this point.

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[A Former User]

Could this be a use-case for Faust when it's ready?

[d.healey]

@Christoph-Hart Thank you, I'll play around with it.

[Christoph Hart]

@iamlamprey said in EQ curve from object.:

Could this be a use-case for Faust when it's ready?

No, not really, Faust is not really suited for spectral processing, it shines in circuit simulation and physical modeling.

Actually I also think that using 30+ bands of peak EQs is not the 100% right way to simulate AET as this amount of filters will smear the phase and is not super efficient (especially if it's per voice). The proper solution would be writing a FFT filter that applies interpolated gain reduction for each FFT bin based on the analysis of the loudest and softest sample:

1. Create a samplemap with two layers (ff and pp)
2. For each note / sample, do an FFT, and compare the gain factor for each bin (should be <1.0 so it only works subtractive)
3. Write that gain factor array into a data file. You can just use audio files to store that, then you can load the data as SFZ into the realtime processor.
4. Ditch the pp layer.
5. Write a FFT processor that applies the gain factor on each bin (the FFT size of the analysis and of the realtime processor must be the same, so you need to find a compromise between latency and frequency resolution).

Everything from 1-4 can be done inside HISE, but for 5. you need to write (or commission) a custom C++ module, but I would say that's rather beginner level spectral processing. Then you need to tweak the parameters to match your use case (FFT window, FFT size, smoothing between bins, etc).