Open source project aims to overhaul music search

Machine learning fuels Sun music recommendation technology

Querying Sun's prototype search engine for Led Zeppelin brings up a list of recommended artists - or "tagomendations" - such as Pink Floyd, Queen, the Rolling Stones and Jimi Hendrix. The user can then click a "why?" button to find out which tags overlap with the recommended artist and the one searched for. Hendrix is recommended for Led Zeppelin fans based on tags like "guitar gods," "classic rock," "guitar virtuoso" and "psychedelic."

In addition to recommendations for other music, the search engine provides links to videos, pictures and upcoming concerts, if the artist searched for is alive and touring.

The tag system is better at analyzing music today than Sun's machine learning algorithms.

"There's so much you can't get out of the audio," Lamere said. "The fact that two songs played during your senior prom means a lot to you, yet it doesn't" factor into sound recognition.

Still, computerized analysis of audio can fill in the gaps when artists are so new they simply aren't being discussed on the Web, he said. In the demonstration, Lamere had Sun's software "listen" to a Mozart piano sonata, and watched it spit out a list of recommended songs, mainly other classical music.

Future advancements to the computerized analysis will enable recognition of major and minor chords, bridges and choruses, and the rhythm patterns of reggae, pop and ska, Lamere said.

While Sun hasn't perfected this type of high-level analysis yet, Lamere isn't getting impatient. "I think I have the most fun job in the world," he said.

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