One of the most attractive functions of music is that it can convey
emotion and modulate a listener's mood. Music can bring to tears,
console us when we are grieving and drive us to love. Music information
behaviour studies have identified emotion as an important criterion used
by people in music searching and organization. Hence, it becomes more
and more significant the role of music emotion recognition. The
automatization of the perceived emotion recognition in music allows
users to organize and to research in a content-centric fashion. Purpose
of this study is to find a link between music and emotions during the
listening of a song by combining audio and physiological signals
analysis. Inclusion of emotions is found to be an hard task, due to the
subjective nature of emotion perception. There are problems in the
reliability of ground truth data and evaluation of prediction results,
all issues that are not present in other data-driven tasks, like for
example face recognition or speech recognition.