@julian said:
If you interpolate data between samples it no longer is a true representation of the original sample. Also if you were to make two consecutive recordings of a piano string being hit by a hammer using the same midi velocity then tried to phase cancel these 100% it just would not happen as a piano is an analogue instrument not a digital waveform.
I wasn't suggesting interpolating data.
However, taking your cancellation example. I am willing to believe that the CEUS is sophistcated and accurate enough that if you programmed it to play the same note in the same way in the same acoustic environment and then tried to phase cancel these, you could achieve in the region of 90% cancellation.
I am also willing to believe that if you got the CEUS to play the same note in the same way but just one velocity layer apart (given that we are talking about 100 velocity layers overall), then and attempted to phase cancel those waves out you could achieve close to 90% cancellation.
And it is basically those sorts of properties that this sample set lends itself to a high compression ratio, regardless of the compression algorithm used (although I'm happy to believe that VSLs algorithm is optimised for this sort of data).
A good benchmark if VSL is willing to try it, would be for someone in VSL to take the full 500GB uncompressed data and put it in a big zip file, and then let us know what compression that achieves. It may not be as good as the 10:1 ratio (and a bit embarrasing for VSL it it turns out better!!), but my suspicion is that it will not be too far off (8:1 - 9:1).
Matthew