Deezer researchers published a paper last week titled, "Music Mood Detection Based on Audio and lyrics with Deep Neural Net," documenting their development of an AI system detecting and classifying the mood of music tracks. In the world of Spotify playlists and YouTube auto play, music listeners are looking for streams that fit both their current mood and the intensity of the feeling. When you're feeling down, there's nothing worse than your sad song playlist being interrupted by nightclub summer bop; let's be real, not every time and place is the right one. Deezer, an international internet music streaming service, has a team of researchers dedicated to understanding how machines recognize track moods and intensities to better service their seven million users. In their research, spotted by Venture Beat, the researchers determined that not only the instrumental presentation of a song is the cause of emotion arousal, but also the song lyrics. In fact, the study states that "both modalities are equally important." The team uses a model depending on deep learning to identify the emotional correlations between 18,000 tracks based on valence and arousal values. The study states that this method is more effective than previous classical approaches, specifically in identifying arousal levels thanks to their analysis of the instrumentals and not just the lyrical content. At the conclusion of this study, the research group opened doors leading to the deeper exploration of obscure content, which will require large sample sizes of so-far inexistent data. More databases will lead to better understood correlations. 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: ambiguity level. In the event that listeners experience the same song differently, the AI could be trained to still form different playlists for each individual based on its correlation with previously played content. Music tailored to your mood in real-time is on its way. Soon, your computer may be able to find you music far better than you can whether it's a calm playlist of sad songs after a breakup or some bumping EDM to celebrate a graduation. In any case, searching yourself for that perfect playlist may soon be a thing of the past.
Researchers are using AI to help music streaming service Deezer better identify what music its users are in the mood for when creating playlists. Researchers dedicated to understanding how software can provide a better user experience have published a paper detailing their approach. 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.