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Like AudioRadar, Search Inside the Music is a media player that measures song features. It displays songs as clumps of “stars” in an imaginary sky, grouped by genre and sound similarity. Users can take a musical “journey” through their collections, clicking on a starting point, say, a fast rock song, and requesting a playlist that moves toward a finale, such as a quiet classical piece, minimizing “whiplash” along the way.

“Massive music collections…are crying out for better navigation mechanisms,” says Columbia’s Ellis. Both AudioRadar and Search Inside the Music are still prototypes, though. The former will be presented at the Sixth International Symposium on Smart Graphics in Vancouver, Canada, later this month.

These programs haven’t left the labs yet mainly because they’re still inefficient. “It takes very long to extract the songs,” says Hilliges, admitting that he has not yet built his prototype to its 10,000 song capacity because he gets “frustrated” during the extraction process. AudioRadar’s slow algorithms cause songs to take, on average, five to ten percent longer than their playing times to process. For large collections, that can amount to many hours.

Stephen Downie, associate professor and specialist in information retrieval and multimedia at the University of Illinois at Urbana-Champaign, thinks this problem is short-lived, though. As computers and extraction algorithms get faster, systems like AudioRadar will eventually “be built into your iPod,” he predicts.

Still, these programs have other glitches. “Similarity is a human metric,” says Lamere, principal researcher on Sun Lab’s music search project, meaning it’s still a subjective phenomenon: people call songs “similar” for a variety of reasons.

Ellis says current computer programs “do a poor job of duplicating human similarity judgments…In large music collections, we frequently encounter machine similarity judgments that just make no sense to a listener – and the more diverse the collection, the more outlandish these misjudgments become.” Early versions of Search Inside the Music, for instance, grouped classical music with heavy metal, because it measured similarities by timbre of instruments. To the computer, harpsichords and heavy-metal guitars sounded similar.

These programs are also limited by a quality that’s even harder to measure: originality. “You as a human will recognize “Stairway to Heaven” played on a banjo, as opposed to the original version played at the Led Zeppelin concert,” says Downie, “but these systems really can’t get it…It’s nice to see that they’re trying to commercialize [these programs],” he says, “but there’s a lot of ground yet to explore.”

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