Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

With the introduction of ChatGPT, the public's perception of AI-generated content has begun
to reshape. Artificial intelligence has significantly reduced the barrier to entry for non …

In music mood prediction, regression models are built to predict values on several mood-
representing dimensions such as valence (level of pleasure) and arousal (level of energy) …

Music listening is an inherently cultural behavior, which may be shaped by users'
backgrounds and contextual characteristics. Due to geographical, socio-economic …

Do people from different cultural backgrounds perceive the mood in music the same way?
How closely do human ratings across different cultures approximate automatic mood …

Most of the previous literature on music users' needs, habits, and interactions with music
information retrieval (MIR) systems focuses on investigating user groups of particular …

Music is omnipresent among human cultures and moves us both physically and emotionally.
The perception of emotions in music is influenced by both psychophysical and cultural …

Music mood recognition (MMR) has attracted much attention in music information retrieval
research, yet there are few MMR studies that focus on non‐Western music. In addition, little …

Music I nformation R etrieval (MIR) evaluation has traditionally focused on system‐centered
approaches where components of MIR systems are evaluated against predefined data sets …

Understanding how music can evoke emotions and in turn affect language use has
significant implications not only in clinical settings but also in the emotional development of …