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by mr_luc
1701 days ago
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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. |
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--- Edit: this one seems simple enough to learn from, it's minimal, MIT licensed, audio-focused, written in Julia, and references the course material that it's based on:
https://github.com/nicholaskl97/wavelets
It, uh ... like lots of scientific code, it has a lot of single-letter variables. :D But if one was to google up a few acronyms ('DWT'), install Julia, get it to run, and then re-implement it in another language, my feeling is that you might understand wavelets pretty good, no? Or be at least be well-equipped to understand more interesting uses of wavelets?
(I'm posting this because I might use some 'shop time' doing approximately that, so I would definitely appreciate any HN comments telling me 'consider learning from $some_other_example instead, for $some_reason.')