@boulderskies The Music Genome Project is a growing collection of music with over 1,000,000 songs. Trained musicians listen to each song and categorize it in terms of hundreds of specific attributes.
For example: Does the lead singer have a breathy voice? How distorted is the rhythm guitar? What key is it in? What tempo? Time signature? Are the lyrics about love? Sex? Loneliness? This comprehensive taxonomy makes it possible to use mathematical heuristic techniques to identify groups of similar songs. Pandora plays songs selected to match the various musicological characteristics of songs selected as inputs by the listener.
Pandora also allows the listener to give feedback on songs that play via "Thumbs up" and "Thumbs down". Thumbs indicate that the listener likes or dislikes one or more elements of that song. The Pandora algorithm responds by playing more songs that share characteristics with the positively rated songs – and fewer songs that sound like the negatively rated songs. Over time, each station will predominantly play songs the listener likes. Thousands of new songs are added to the collection every week. Those that share characteristics of songs positively rated by the listener will play too. Specific details on the inner workings of the MGP and Pandora algorithm's are mostly confidential.
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thank you Adam. good write-up. i also viewed several videos of Tim Westergren that were very interesting.
scott
Always happy to help, @boulderskies! 😁
>>Check out: The Listener Lounge: August 2024
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@AdamPandora , Fascinating writeup. I’d be curious to know what the approximately 450 attributes are. It would be cool if I could create a station based on, say, 12 of those attributes of my choosing. (12 is just a random number for this example.)
Probably outside your purview, but is there a reason that such a compilation must be proprietary?
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I think this is a different Genome Project involving genetics and DNA, @alvitubit23.
You can find out more details about the Music Genome Project in these blog posts on the Pandora Community:
@boulderskies Looks like these articles were posted after your original thread post. @blankface you may be interested in checking them out too. 🎧