  Deep learning models for music have advanced drastically in the last few
years. But how good are machine learning models at capturing emotion these days
and what challenges are researchers facing? In this paper, we provide a
comprehensive overview of the available music-emotion datasets and discuss
evaluation standards as well as competitions in the field. We also provide a
brief overview of various types of music emotion prediction models that have
been built over the years, offering insights into the diverse approaches within
the field. Through this examination, we highlight the challenges that persist
in accurately capturing emotion in music. Recognizing the dynamic nature of
this field, we have complemented our findings with an accompanying GitHub
repository. This repository contains a comprehensive list of music emotion
datasets and recent predictive models.
