Global Music Data
Building Blocks Driving Great Music Experiences
Gracenote Global Music Data is the most comprehensive collection of factual and descriptive metadata for the most popular music worldwide. With deep, clean data and standardized artist and recording IDs, Gracenote enables entertainment services to simplify how fans find, discover, and connect with more of the music they love.
Artists, Albums, and normalized Recordings for the most popular content globally with relational links for entertainment services to create a smarter “Guide for Music”
Key editorial descriptors such as Genre, Origin, Era, and Artist Type, and key sonic descriptors such as Mood, Style, and Tempo enable better playlisting and discovery
Gracenote IDs allow fans to discover more of the music they love by linking them to artist appearances on late-night TV, roles in movies, and music videos
Gracenote Global Music Data features deep and rich descriptors for the most popular music worldwide. Leveraging Gracenote’s advanced machine learning technology combined with the industry’s finest editorial team, Gracenote descriptor data for Genre, Origin, Era, Artist Type, as well as for Sonic Mood, Sonic Style, and Tempo is the secret sauce behind the world’s hottest playlists.
Gracenote has become one of the best examples for the music industry’s increasing reliance on artificial intelligence.
Gracenote Sonic Style
Gracenote is revolutionizing how the world’s music is organized and discovered. Gracenote Sonic Style is a breakthrough new music descriptor system that uses machine learning to classify the “Style” of music at track-level across massive catalogs – for the first time ever.
Powering Voice and Text Search
In this era of connected IoT devices, finding your favorite jams no longer requires typing an artist name into a search bar. Gracenote Global Music Data provides structure, in the form of IDs and normalized data, to support the most innovative music search and discovery interfaces, from voice and gesture to virtual reality and beyond.