Shazam is likely a bit more complicated and accurate since you’re sending data to an online service and you actively check a song at any time.
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tubthumper@lemmy.world 1 week agoThank you for giving me more background here! I was vaguely aware of this feature but believe I disabled it earlier on (along with other unused features and app permissions en masse) so the surprise app was a shock. I’m tech-aware but not savvy at this point so I just risk mitigate where I can.
I don’t have experience with Shazam or similar for context, so do most apps like this utilize snippet hashes on device? (headed to wiki but thought I’d ask)
MrScottyTay@sh.itjust.works 1 week ago
Augmented1207@feddit.org 1 week ago
I read up about it a while back, so anyone pleas correct me. It works like this I think: An audio sample is recorded, chunked into overlapping windows, which are converted into a spectagram (the black, blue, yellow, red image of frequency vs time). Idk at which point what is send to the server but to me it would make sense to keep the data amount low by sending after the next step: From the spectagram, the algorithm searches for high spots or notable “pixels” in the spectagram. It then notes the relative position between many spots, not only the next but lets say 10 per spot (propably more, as just a pair of 2 numbers are super cheap and small). We then hash these relative vectors. So we now have a list of frequency vs time vectors hashed in unique strings of our recorded audio windows. In the database we have all songs send through the same algorithm and stored. We then just compare our hashes from the recording to the database and find the song with the most matches.
Its pretty smart and I suppose there are additional filters to speed up the process and make it more reliable. Its just so simple, I love it