Wednesday, April 15, 2009 | Luke Barrington wanted a good example of “funky music with a horn section for listening to at a party.”
The University of California, San Diego doctoral student typed the search term into his computer program and it told him to give James Brown’s “Give It Up Or Turn It Loose” a try. It also suggested “Onyoghasayo” by Shankin’ Pickle and “Super Freak” by Rick James.
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.
“You don’t need the artist name; you don’t need the song name, all you need to say is ‘I want some scary Halloween music,'” said Lanckriet, an electrical and computer engineering assistant professor at UCSD’s Jacobs School of Engineering.
Machine listening is part of the latest evolutionary cycle in how people find, compile and listen to music. Personalized playlists, rooted in the mix cassette tapes of the 1980s, have, among younger audiences, largely taken the place of albums put out by record companies.