Researchers are using AI to help music streaming service Deezer better identify what music its users are in the mood for when creating playlists. The company is working with a team of researchers at Carnegie Mellon University (CMU) and Stanford University, who have developed an algorithm that can analyze data from millions of songs on Spotify and other services like Apple The team said its deep learning models had identified "correlations" between 18,000 songs, and concluded the lyrics were just important as the melody when catching a listener's ear. For example, in addition to the tracks within a database being labeled with mood and intensity, there could be a tertiary category for the AI to analyze: Deezer aims to use AI to select songs using "ambiguity", based on the different reactions to tunes in previous playlists.
Researchers are using AI to help music streaming service Deezer better identify what music its users are in the mood for when creating playlists. The company is working with a team of researchers at Carnegie Mellon University (CMU) and Stanford University, who have developed an algorithm that can analyze data from millions of songs on Spotify and other services like Apple The team said its deep learning models had identified "correlations" between 18,000 songs, and concluded the lyrics were just important as the melody when catching a listener's ear. Deezer aims to use AI to select songs using "ambiguity", based on the different reactions to tunes in previous playlists.