Proposal for new music analysis algorithm with very practical uses inside Amarok

[Sven Krohlas]

Hi Erik, Soren,

> So, what it is: [ButterScotch Butterscotch] is an algorithm to fingerprint 
> songs which is not designed to provide an unique ID for a file (technically, 
> it can as long as the file has not been transcoded or you have the first 2 
> minutes of audio, but that's not the point).  Read again: it is NOT like MB or 
> liblastfm or [http://mail.kde.org/pipermail/amarok/2008-August/006488.html 
> Soren's patch].
> 
> Butterscotch's unique property -- what makes Butterscotch interesting -- is 
> that it lets you identify "duplicates".  Let me illustrate by example: let's 
> assume you have a track named "What hurts the most" in MP3 format 128 kbps, 
> from an album you ripped that is called "Perfect day", and that you have 
> another track "What hurts the most (radio mix U.S.)" from an album called 
> "What hurts the most CD maxi" that you ripped in FLAC lossless.  Now, upon 
> listening, you will discover that those are the exact same tracks, maybe one 
> of them starts half a second later, but they sound exactly the same (except 
> for the maxi cut being in perfect CD quality).  Butterscotch will tell you 
> beyond a doubt that those songs are the same using simple math (correlation 
> coefficient averages).

I guess most of us don't know much about music similarity recognition
(including me), so there aren't many replies here, yet. For me there is
one important question: is it possible to use one algorithm (and so one
fingerprint) for your use cases and Sorens?
Calculating a fingerprint takes a relatively long time, I guess, and
collections grow really fast these days.

Your algorithm can find duplicates, can it also tell me "how much" a song
sounds different from another like Sorens does?
And, on the other side, if Sorens algorithm can tell me how much two songs
sound alike: duplicates should be very close here, right?

I don't know much in that area, so forgive me if I ask trivial questions
from your pov.

cu
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