Paul Lamere schreibt sich auf seinem Blog Music Machinery über kleinere und größere Musik-Hacks – im Sinne von schnell zusammengestöpselten Programmen. Meistens benutzt er dabei die Programmierschnittstellen von z.B. Spotify oder The Echo Nest (wo er auch seine Brötchen verdient). Dabei kommen oft interessante Tools heraus, hier zum Beispiel die Drop Machine, die automatisch erkennen kann, an welcher Stelle in einem Song der Drop kommt – und zwar ganz ohne die Musik selbst zu analysieren:
The Drop Machine takes a very different approach – it crowd sources the finding of the drop. And it turns out, the crowd knows exactly where the drop is. So how do we crowd source finding the drop? Well, every time you scrub your music player to play a particular bit of music on Spotify, that scrubbing is anonymously logged. If you scrub to the chorus or the guitar solo or the epic drop, it is noted in the logs. When one person scrubs to a particular point in a song, we learn a tiny bit about how that person feels about that part of the song – perhaps they like it more than the part that they are skipping over – or perhaps they are trying to learn the lyrics or the guitar fingering for that part of the song. Who’s to say? On an individual level, this data wouldn’t mean much. The cool part comes from the anonymous aggregate behavior of millions of listeners, from which a really detailed map of the song emerges. People scrub to just before the best parts of the song to listen to them.