Electrical engineers at UC San Diego have created a new breed of search engine for music (as well as Facebook games that provide researchers with the information needed to improve the new search en...
Electrical engineers at UC San Diego have created a new breed of search engine for music (as well as Facebook games that provide researchers with the information needed to improve the new search engine). This video highlights the capabilities of the new music search engine (http://herdit.org/music/index.html), which will be available for beta testing next week. Register for the music search engine beta test at: http://herdit.org/music/
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I wondered about this classification too. How does the algorithm deal with songs with multiple movements like The End to a Sad Film? The first part (more upbeat) might be classified as waking up music, but the later parts of the song are tragic like Vigilant described.
We have an algorithm that can automatically divide a song up into homogenous segments like chorus / verse / bridge etc. Then we tag each segment separately. The trick is how to combine these segments together? Do you just add / average the description for the chorus and the verse? Or do tell listeners "the verse of this song matches your query for a mellow piano ballad " (but then, in the verse, crazy guitars kick in!)
Yeah, Pandora would be a great source of data to train the algorithm on. Pandora could also benefit a LOT from a computer that could automatically add new songs to their database - right now it takes about 30mins for a human to listen to the music and annotate it before Pandora can add a song. Means that new / unknown bands are never going to make it...
I am not used to waking up to the sound of a sad film. Why did the algorithm decide to wake up to Nickolaus Mueller's tragic song? I'd rather rather wake up to "Oversleeping" by I'm From Barcelona or "Up, Up, and Away" by KiD CuDi.
Five stars though! I fully support this research. Ideally Pandora would fund this research. There would be tremendous synergy from having a professionally tagged database to train your algorithm on.
Autoshare makes certain YouTube activities public on the services you choose. Select only the services you are comfortable with - like Facebook, Twitter, or Google Reader - to let your friends know what you like on YouTube. You can turn Autoshare off at any time.
We have an algorithm that can automatically divide a song up into homogenous segments like chorus / verse / bridge etc. Then we tag each segment separately. The trick is how to combine these segments together? Do you just add / average the description for the chorus and the verse? Or do tell listeners "the verse of this song matches your query for a mellow piano ballad " (but then, in the verse, crazy guitars kick in!)
Means that new / unknown bands are never going to make it...
Five stars though! I fully support this research. Ideally Pandora would fund this research. There would be tremendous synergy from having a professionally tagged database to train your algorithm on.