Here’s some performance footage of the corpus-based sampler in action.
So this is 3094 samples that are all pre-analyzed and then being played by by audio analysis coming from the SP pickup and a DPA 4060. So rather than individually mapping samples to zones or regions (or things like center-to-edge), the loudness, brightness (spectral centroid) and noisiness (spectral flatness) of each attack is used to find the nearest match from the sample database.
Not only is this super expressive, but it’s much easier to setup since you don’t have to decide on what samples you want, you don’t have to setup splits, round robins etc…