We analyze and identify collaboration profiles in successbased music genre networks. Such
networks are built upon data recently collected from both global and regional Spotify weekly …

We present PECMAE an interpretable model for music audio classification based on
prototype learning. Our model is based on a previous method, APNet, which jointly learns an …

This paper surveys 560 publications about music genre recognition (MGR) published
between 2013–2022, complementing the comprehensive survey of [474], which covered the …

Annotating music items with music genres is crucial for music recommendation and
information retrieval, yet challenging given that music genres are subjective concepts …

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 …

Musical genres are inherently ambiguous and difficult to define. Even more so is the task of
establishing how genres relate to one another. Yet, genre is perhaps the most common and …

As the music industry becomes more complex, reaching a wider audience through
collaboration is effective in maintaining the relevance of artists from distinct genres in the …

Au sein de cette démonstration, nous présentons Muzeeglot, une interface web permettant
de visualiser des espaces de représentations de genres musicaux provenant de sources …

Au sein de cette démonstration, nous présentons Muzeeglot, une interface web permettant
de visualiser des espaces de représentations de genres musicaux provenant de sources …