This is the stuff I want to know more about, because I understand my analogies/mental model, but I have only crude/naive 'code mental model' of how these kinds of things are implemented

When you say:

    When you scan this wavelet across the audio file

Is that literal in code?

Apologies for the naive code analogies -- your comment makes me think of something like an XLA 'reduceWindow' operation (edit: or an OpenCL kernel), where a wavelet-sized 'window' is slid over the input, the difference is computed for each data point -- and then (waves hands: probably something smarter than just a) 'cumulative sum' to see how close/different is is.

(a) is that on the right track/what you meant by 'scanning the wavelet across?

(b) what about transforming the wavelet -- to different scales, etc?

This seems like the kind of thing that's actually like a search problem, heh, where you'd need to slide it over the input many many times, and where it could conceivably benefit from (waves hands) machine learning techniques as a result, to come up with something that does the search for a good wavelet encoding more efficiently based on the input.