@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:
Create a samplemap with two layers (ff and pp) For each note / sample, do an FFT, and compare the gain factor for each bin (should be <1.0 so it only works subtractive) 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. Ditch the pp layer. 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).
