Audio hashing (acoustic fingerprinting) already exist for detection of copyrighted music and are more efficient. See Shazam

Shazam produces an embarrassing number of false matches, which I assume are hash collisions or something similar in the world of their fingerprinting system?

> False match? Sorry! Please lodge a complaint for manual review.

> Nb: complaints require an account in good standing at as this is your third strike your account is now suspended.

Near enough is good enough for most people paying-for/selling the tech.

Shazams correct hit rate has certainly lowered in the many years I've been using it. Presumably because the pool of music it now is being asked to decipher is becoming unwieldy.

I am permanently pleased to learn one size does not fit all even in gargantuan saas companies.

Is there a need for that? Content id seems to work well enough

I doubt it will be that simple. Audio fingerprinting a la Shazam works by identifying key elements in some transformation of the sound, and setting some threshold for the number of matches. I suppose the output of this compression method offers a good way for identifying a song by a bit of sound, but the identification algorithm will be much more complex.

I'd like to see what happens when you modify the stream. If the representation is really that compact, making small changes should change the output considerably. Treat it like a synthesizer, really. That should tell us something about its usefulness in identifying audio.