I guess just thinking about it in terms of the spectral compensation stuff. Where the live snare is the “target” that I’m trying to get the sample to sound like. (Unless I flipped the terminology there too…)
You mean just as a way to avoid using a parallel coll or entrymatcher? Wouldn’t the second dataset here be functioning that way? (taking an exact index and returning the values associated with that index)
So if I understand you correctly, I have a dataset with target transients in it, I query that with my real-time incoming target transients and that returns a value like 15. As in, that target transient is most like entry 15 in the dataset. Then I just need to go fetch the corresponding target attack to further query with. Is that correct?
I’m in the middle of creating the samples for the dataset (with variations for descriptors, mfccs, etc…) so I haven’t yet built the bit for proper matching yet, but do you think that building a KDTree with loads of entries with just a single training point each will be alright?