Spectral Processing Experiment
Click to see screenshot of Audiomulch setup
It is easy to do multiple things in the frequency domain that would be expensive if applied using convolution in the time domain. Duplicating frequency bands, creating side bands, delaying frequencies, etc... all only require a high resolution FFT -> {your frequency gunk} -> iFFT. Of course, the FFT/iFFT adds latency you wouldn't get with a discrete linear convolution in the FIR and block convolution approach. As you well know, if you FFT, depending how you FFT, you'll impose a sample latency of at least 2 x the nyquist, or, if blocking, particularly with a SIFT approach, FFTSize - FFTSize / Overlap Factor samples.
Of course, any zero-delay convolution algorithm only gives you 0 latency if your CPU usage increases as the algorithm is worked through -- which is why the CPU usage for longer-tail convolving reverbs is so high while short ones is less.
So, with the FFT approach, you impose a 1 time delay, and make it less expensive to do many operations (i.e. did you know that frequency multiplication is actually equivalent to a circular convolution?) -- or you can use CPU like it was made of sand and get zero latency with a zero delay time domain convolution.
Still, apparently you can have your cake and eat it too, ... with a caveat..., if I interpret what Bill Gardner wrote in 1995 in the Journal of the Audio Engineering Society, if you are happy with imposing a penalty of a block of N samples, in which case you can do your convolutoin in 34 log2(n) time! That's pretty fast! For a 3 second block at 44.1khz (132300 points), each output sample would need 428 multiplies. Fun Stuff!
Trans-modern music is all a matter of compromises my farties.


