Looking for the Slow Build in the Million Song Dataset

Interesting approach but a lot of songs I would consider falling into this category score very low:

Here are a few examples from the original reddit post[1]:

  Song (Correlation)

  The Velvet Underground - Heroin (2.95)
  The Beatles - A Day In The Life (0.00)

Other songs with low correlation:

  Lynyrd Skynyrd - Free Bird (0.38)
  Metallica - Hero Of The Day (3.72), One(3.47)

I think the reason is that tempo and compression (which I associate with tension) are not taken into account but play a big part in our hearing experience. This data may be harder to extract, though. Anyway interesting work!

[1]: http://www.reddit.com/r/Music/comments/hnc3b/what_is_your_fa...

Others come to mind:

Ravel's Bolero has a "huge build" at least in some versions: http://labs.echonest.com/loud/?songId=SOKNXIQ13134384E1B

Metallica's To Live Is to Die actually has quite a quick build http://labs.echonest.com/loud/?artist=&title=to+live+is+...

Godspeed you! Black Emperor's works are more ebb and flow than sustained build throughout the track http://labs.echonest.com/loud/?songId=SOJBUTX1311AFDAC27

I find this truly amazing, not because of the technologies involved, but mostly because I find it fascinating that we can now easily process a library of over a million song and find which have a “slow build”.

This is very cool - one quibble though, there doesn't seem to be any test of 'slow' in the slow build. You could add a linear regression slope and select for songs where Pearson coefficient is high, the slope is small and the last decile volume/first decile volume is high is large.