Yeah there's quite a bit of opportunity to reduce processing time along the way.
Couple cool things I've learned about bats.
- They are *extremely* loud in the ultrasound range, 130db echolocation calls from something the size of a mouse.
- On an average recording, the ultrasonic range is almost exclusively filled with sound from wildlife (bugs, birds, etc). I'd expected to see lots of harmonics and whatnot from human-generated sounds but there just aren't that many. It's quiet up there.
- You can leverage these two in combination for sampling by just strapping the recording device to the roof of your car and driving around. The wind and road noise is basically absent and the echolocation calls come through loud and clear. The AudioMoth can be fitted with a GPS receiver to correlate the calls to location (and time ofc)
- There are three primary types of echolocation calls: Search - Semiregular calls just to see what's out there. Approach - Faster rate of calls once prey has been identified. Terminal - Aka feeding buzz, very high rate (200hz) of echolocation calls in the last meter or so of approach. Most of the recordings of bat calls you see on YouTube are slowed down 10x to bring the audio into listening range, but this also slows the call tempo by just as much. They make lots of calls.
- Most bat calls use frequency sweeps rather than continuous tones to pick up both distance and relative velocity of the target (akin to FMCW radar).
- There are more bats around than I realized. I started off by looking for 'good spots', but now I just set the device out on a porch. Many times you'll hear me walking up to the recording device at the end of a recording and there will be 2-3 bats overhead that I was perfectly unaware of.
Thanks jcims for sharing this amazing info! However, I wonder how these very loud bats, all in close proximity, don't get confused by each others' calls? Is the answer their frequency sweeping? Or does each have something analogous to a unique "voice"?
Good question! Yes they definitely have unique voices and call signatures. A single string of calls from a single bat will have variation between calls as well (especially in search phase).
It'd imagine there's a lot of neurophysical adaptation involved as well, just like listening to a single conversation in a crowded room.
That said, hunting in an area filled with bats is probably not as effective as being in a quiet place.
I found it interesting, that Git itself has built in similarity notion... when it packs objects, it groups files by path+size, runs delta cmpression to find which are close.
This might help if interested - https://vectree.io/c/implementation-details-of-stdio-and-sse...
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