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Decoding the Algorithm for Pop Music
fb4f writes "Over at Modplug, they have an article describing a mathematical algorithm to predict if a given song will become a hit or not. Paraphrasing the article, a Spanish company called Polyphonic HMI has made a business out of analyzing song submissions and predicting their "hitability". Here's their description of the algorithm and here's their FAQ. They claim to have predicted the commercial success of Norah Jones through this method. Here's my question (which is not fully answered in their FAQ): if they (music company executives) are currently using the algorithm to screen submissions for their "hitability", can we (people who listen to music) use the same algorithm to reject recycled tunes and encourage originality? I for one, still like the fresh talent and community feel of the tracking scene."
"Here's my question (which is not fully answered in their FAQ): if they (music company executives) are currently using the algorithm to screen submissions for their "hitability", can we (people who listen to music) use the same algorithm to reject recycled tunes and encourage originality?"
And here's my question: can we use this algorithm to create the hit, instead of determining wether or not it's gonna be a hit?
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AFAIK, this isn't new. This technique has been in use for years, at least theoretically.
IIRC, this was first tested on random samplings of classical music. Beethoven and Mozart scored significantly better that others.
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(i know, this is a bit offtopic, but hey!, why not?)
A few years ago I saw an interview of a "composer" (forgot his name). They're guys who are somewhat famous because their name is in a lot of albums, but in very small print: they compose the actual music that the band plays. This is standard practice, apparently.
Anyway the point is that the guy pointed out that most pop tunes were rehashes of older pop hits. Maybe you create a different style with different instruments or beat, but the underlying melody is the same. He then showed some examples, in how some modern R&B titles were lifted off some older Rock titles. It's not that hard to believe though, look at how Puff Daddy makes a living out of talking fast over music of old hits.
So in short, one way to predict if a music will be a hit is by creating a database of previous hits and test the correlation...
[and then of course, there's those who say that Classical music tried every combination possible, so nothing can be new afterwards - but that's maybe a little extreme].
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The article states:
"This software will compare the song to a database that contains the "top-30" hit songs of the past five years in order to search for mathematical similarities. The algorithm then assigns each song a score between one and 10. Any song rated more than seven is likely to become a hit."
Now think about this.. use musical eras like the 80's and early 90's as an example because it's reasonably safe to assume this technology didn't exist at that point.
Look at the charts in 5 year chunks, it all sounds the same. In the 80's, everyone either used a synthesizer or had a raging, face-melting solo at some point in the song. Or the early 90's, "grunge" was being pounded into our head incessantly.
It was like that because it was popular. Band X makes it big, and suddenly Bands X1 through X255 appear on the charts mimicing this sound. This seems to happen in, amazingly enough, cycles of 5 years.
Seems to me this software does nothing to show the "hitability" of a song, but rather telling you whether or not it sounds just like what's currently popular, and has been for the past couple years.
Seems about as magical to me as as an algrorythm claiming it can detect boys that like looking at porn.
Out of sheer boredom, I actually tried to do this sometime this summer. I took a bunch (something around 20) of SCO stories and read all the +4/+5 comments. Surprise surprise, the overall situation wasn't really as bad as I thought it would be. Yes, there were some patterns in what was said, but even if someone did get modded up for saying something that was obvious they always had some argumentation supporting what they said. Simple bashing might get you modded up for a moment, but you'll be modded down the moment someone posts an intelligent reply.
Hell is not other people; it is yourself. - Ludwig Wittgenstein
Someone should make a program that when you ask it to, downloads a story (showing all comments and with the number per page at max so it doesn't have to spider and piss off slashcode) and splits the comments into -1, 0, 1, 2, 3, 4, 5 "buckets" and creates a spam filter. Then, you can apply it to other stories. Sorting by topic would be good, since saying Windows in an Apple story has a good chance of being a flame (or maybe a comparison), but saying it in a story about Longhorn [sucks] probably is less important.
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