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The Music Genome Project, created in January 2000, is an effort founded by Will Glaser, Jon Kraft, and Tim Westergren to "capture the essence of music at the fundamental level" using almost 400 attributes to describe songs and a complex mathematical algorithm to organize them. The company Savage Beast Technologies was formed to run the project.[1]
A given song is represented by a vector (a list of attributes) containing approximately 150 "genes" (analogous to trait-determining genes for organisms in the field of genetics). Each gene corresponds to a characteristic of the music, for example, gender of lead vocalist, level of distortion on the electric guitar, type of background vocals, etc. Rock and pop songs have 150 genes, rap songs have 350, and jazz songs have approximately 400. Other genres of music, such as world and classical music, have 300–500 genes. The system depends on a sufficient number of genes to render useful results. Each gene is assigned a number between 1 and 5, in half-integer increments.[2]
Given the vector of one or more songs, a list of other similar songs is constructed using a distance function.
To create a song's genome, it is analyzed by a musician in a process that takes 20 to 30 minutes per song. Ten percent of songs are analyzed by more than one technician to ensure conformity with the standards, i.e., reliability.
The technology is currently used by Pandora to play music for Internet users based on their preferences. Because of licensing restrictions, Pandora is available only to users whose location is reported to be in the USA by Pandora's geolocation software.[3]
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