Music streaming services give access to more than 60 million songs, but the biggest part remains undiscovered because search functions are limited, playlists are predefined and recommendation engines work on an “other users have also heard” basis. Thus, users are locked in filter bubbles. That is why we need music discovery tools that both work with musical and sound features but adapt to the personal musical taste of users. These tools can help them escape their musical filter bubble and support content creators to become discoverable.
Musicube is an SME that builds AI software for audio and especially music. Musicube developed neural networks that process audio files and automatically tag them with musical features, sound features and emotions. The business model is B2B, so that companies from the media sector use Musicube’s Auto-Tagging Software to enrich their metadata or semantic music search to find music by its features (e.g. “fast and happy songs with acoustic guitar and female vocals”).
In the AI Empathic DJ project, we intend to further develop this software to adapt to listener’s perspectives on music. For example, when searching for “relaxing songs” the musicube engine currently suggests typically ambient relaxing music. However, different people find different styles relaxing, as for example Jazz and Heavy Metal fans. We want to further develop our AI to learn musical tastes and adapt to it. The AI can make personalised suggestions based on a small sample and become the person’s own perfect empathic DJ. Technically, the “empathy” for a user’s perspective on music is achieved by a reduction of the neural network’s (AI’s) own view on music. Musicube’s current neural net produces a Euclidean space of about 500 dimensions and localises all songs in that space. A specific musical taste can be defined as a subspace of this total knowledge. Starting from points inside this user’s subspace (also known as taste or perspective), semantic music search or recommendations can be made that are outside a user’s scope but inside his or her own view on music. This way death metal fans get other search results for “aggressive” music than HipHop fans, just to name an example.
The AI Empathic DJ will be a module that can be integrated in musicube’s existing services, but also in third party software like streaming services and the AI4Media ecosystem.see website