Is Lady Gaga's "Born This Way" a happy song? Is "Bohemian Rhapsody" sad? Gert Lanckriet wants computers to be able to tell. Then people could search for tunes that match a particular mood or instrumental style, and an online store could make better recommendations.

Lanckriet, an associate professor in the Department of Electrical and Computer Engineering at the University of California, San Diego, started by having his computers analyze a collection of 500 popular songs that human judges had categorized in six ways—by genre and tempo, for example. When fed a new piece of music not in the database, the computer uses that training to infer how a human would characterize it. Lanckriet continues to train the system through a Facebook game called Herd It, launched in 2009. Players listen to snippets of music and win points if they agree with the majority of their fellow users; the results are fed into Lanckriet's software.

After the software gets some more fine-tuning, Lanckriet plans to let it crawl the Web like a search engine, automatically classifying the huge amount of music available online. He's also exploring how to use the sensors in smart phones to cue up exactly the sort of music someone is in the mood for. If the phone's accelerometer detects that the user is exercising, it could choose something energetic, while sitting in a quiet room at night might lead it to choose something mellower. —Kenrick Vezina