The most common way to listen to recorded music nowadays is via streaming platforms,
which provide access to tens of millions of tracks. To assist users in effectively browsing …

We present a platform and a dataset to help research on Music Emotion Recognition (MER).
We developed the Music Enthusiasts platform aiming to improve the gathering and analysis …

Music streaming services heavily rely on recommender systems to improve their users'
experience, by hel** them navigate through a large musical catalog and discover new …

The streaming service Deezer heavily relies on the search to help users navigate through its
extensive music catalog. Nonetheless, it is primarily designed to find specific items and does …

Song embeddings are a key component of most music recommendation engines. In this
work, we study the hyper-parameter optimization of behavioral song embeddings based on …

The music genre perception expressed through human annotations of artists or albums
varies significantly across language-bound cultures. These variations cannot be modeled as …

In the realm of digital music, using tags to efficiently organize and retrieve music from
extensive databases is crucial for music catalog owners. Human tagging by experts is labor …

''Why do they keep recommending me this music track?''''Why did our system recommend
these tracks to users?''Nowadays, streaming platforms are the most common way to listen to …

Abstract Music Recommender Systems (MRS) are essential components of online music
platforms, offering users personalized music recommendations from vast catalogs. Despite …

The deliverable reports on the creation of multilingual corpora for Polifonia covering Italian,
English, French and Spanish. Using the methodology of corpus linguistics, a corpus was …