Okay, if you and your friend agree on which 5-sec portion to compare (e.g. always use the first 5 sec, not counting any initial silence that might be present), then you have a fairly good chance of building a DFT-based discriminator/identifier with a pretty good success rate.

In this case, Perl could be very handy for driving the DFT/VQ engine on your friend's audio file, doing data reduction on that output, and running or maybe even computing the suitable statistics to identify a "best match" in your local database of first-5-sec snippets.

Just building your local database of "song signatures" will be a very instructive exercise, and you can use it for both "training" and "testing". I could go on... but it would all be speculative, and you should work it out for yourself.

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