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Back in April I wrote about “Herd It,” a next-level music search engine developed by University of California, San Diego professor Gert Lanckriet and doctoral students Luke Barrington and Damien O’Malley.
As a quick refresher, here is an excerpt:
For years now, computer-based song aggregators like Pandora and Last.fm have allowed people to compile playlists based on song names or artists. But Barrington’s computer at the California Institute for Telecommunications and Information Technology takes things to a new level.
The “black box,” as Barrington’s professor Gert Lanckriet calls it, can listen to a song and decide, for example, whether it is a romantic song or a dance song. It can figure out what genre it falls into, and know what instruments are being played. And it puts the student/professor team at the forefront of the burgeoning field of machine listening. …
They came up with what is best-described as a word/song association game in which players assign words to describe the songs they hear. Players score points based on how similar their answers are to those of other players. The scientists launched the game, called Herd It, on Facebook this week. The goal is to collect about 1 million word/song associations.
At the time I wrote the story, the game was still in its alpha launch phase while the guys worked out the bugs. Play time is over.