Gracenote Unveils Rhythm For Internet Radio

Gracenote has Rhythm, and they want to share it with the developer community. The new Gracenote Rhythm platform provides developers with new recommendation algorithms, powered by big music data, to build the next wave of killer Internet Radio Apps and services. The API will be made available to commercial customers and developers in February 2014.

Gracenote Rhythm harnesses the power of the world's largest source of music metadata, a global team of music experts and Gracenote-powered algorithms to form the backbone for Internet Radio services. When plugged into a music catalog, it gives developers the ability to create radio stations based on "seed" artists, songs, moods and genres with adaptive controls for "like" and "dislike," ensuring next-generation radio stations get smarter and more personalized the more they are used.  Developers will also control radio-tuning features that allow music fans to dial up more popular artists or dial down to receive more obscure, indie artists and tracks.

"The music industry has seen a lot of music services come and go with the exact same Internet Radio solutions that rely heavily on Web-scraped and auto-generated content. We'd like to see some real innovation in the market," said Stephen White, president of Gracenote. "At Gracenote, we believe there has to be a human component to creating and delivering Internet Radio - technology can't do it alone. The real magic behind Gracenote Rhythm is our unique mix of music experts and machine processes to create world-class radio."

Gracenote Rhythm will tap into descriptive music metadata covering more than 180 million tracks from around the globe. This data intelligence is aided by editorial feedback from Gracenote's global team of music experts – real people with deep knowledge of regional music trends. Combined, Gracenote's metadata, editorial expertise and powerful new algorithms will craft beautiful music stations and channels across all genres.

Gracenote descriptive music metadata focuses on six main categories:

• Genre of the song
• Mood  
• Era the song was recorded
• Tempo
• Origin or region most associated with the artist
• Artist type

These descriptive music characteristics are used to make deep connections between artists and tracks, creating radio stations based on similar songs and artists. Popularity and trending data are layered in to help listeners uncover new and emerging artists and tracks.