A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
XXV Congresso de Iniciação Científica da Unicamp
In this work, we assessed the impact of using genre information in the automatic classification of perceived emotion in music. In this process, we developed a dataset in which tracks were mapped according to their genre and their perceived emotion. Our results show that using a specific classifier for each genre yields better results than using a single classifier, with no genre information, for Indie-Rock, Jazz, Heavy-Metal, and Classical music. However, classification result were poor fordoi:10.19146/pibic-2017-77932 fatcat:kholx275rbgzhbvyftfpci3m5a