The music industry has been in trouble for decades. There’s a lot of reasons. But here’s an interesting advancement:
It seems that Sun has built ‘one of the best music similarity algorithms’ that’s based on the actual sound, with machine learning that analyzes features such as frequency and beats per minute to map out the rhythm structure, and determine the genre and which instruments are playing, Lamere said. Sun has taken advantage of prior research into speech recognition technology to tease out the features that correspond with the timbre of music and can be measured with computers, he said.”
A music store like Apple iTunes contains more than 5 million songs today. And there are plenty of similar music stores online. With people posting online their own creations or excerpts of the concerts they attend, it’s possible that a million new songs appear every day in a near future on the web. So how will you find new music you like? Right now, two approaches are prevalent: Amazon and other sites use collaborative filtering while Pandora and others use content matching. Both approaches are time-consuming, using both humans and computers. Now, according to Network World, Sun Microsystems is about to release an open source music recommendation technology far superior to current systems and totally automated. Read more…
A new music recommendation system from Sun | Emerging Technology Trends | ZDNet.com
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