Nielsen-owned Gracenote has announced the launch of an artificial intelligence service called Sonic Style that will sort massive catalogs of music by style for the first time ever. Sonic Style will classify 90 million songs not by the genre of music the artist is known for, but rather the actual style of each individual recording. Music has typically categorized by artist genres, such as rock or hip hop. However, artist genres alone do not always tell the full story of an artist's full catalog or career. Gracenote has developed nearly 450 Sonic Style descriptor values.

Sonic Style is hoping to shake up the way music is traditionally categorized, moving past the typical overarching genres like rock or hip-hop to classify each song on a granular level. To that end, Gracenote has amassed nearly 450 Sonic Style descriptors that create a "style profile" of each recording and can pair machine learning descriptors such as tempo and mood with editorial ones, like artist genre, era, and origin. For example, the press release suggests the service can mine through Taylor Swift's catalogue to figure out which songs are more pop, more country, more pop electronica, or god help us, more R&B. That level of musical understanding will hopefully help smart speakers, voice assistants, streaming services, and, yes, even measly humans create better, more personalized playlists. "Sonic Style applies neural network-powered machine learning to the world's music catalogs, enabling Gracenote to deliver granular views of musical styles across complete music catalogs," says Brian Hamilton, Gracenote's general manager of music and auto, in a statement.

Sonic Style is hoping to shake up the way music is traditionally categorized, moving past the typical overarching genres like rock or hip-hop to classify each song on a granular level. To that end, Gracenote has amassed nearly 450 Sonic Style descriptors that create a "style profile" of each recording and can pair machine learning descriptors such as tempo and mood with editorial ones, like artist genre, era, and origin. For example, the press release suggests the service can mine through Taylor Swift's catalogue to figure out which songs are more pop, more country, more pop electronica, or god help us, more R&B. That level of musical understanding will hopefully help smart speakers, voice assistants, streaming services, and, yes, even measly humans create better, more personalized playlists. "Sonic Style applies neural network-powered machine learning to the world's music catalogs, enabling Gracenote to deliver granular views of musical styles across complete music catalogs," says Brian Hamilton, Gracenote's general manager of music and auto, in a statement.