Music classification based on genre and mood

Abstract

The advent of internet and the growing number of digital media has increased the necessity of Music Information Retrieval systems within which Music Classification is a prominent task. Here, we present methods to perform genre based classification over five different genre and mood based classification using a mood model that maps mood onto a two-dimensional space along axes of arousal and valence. Support vector machine and a feed-forward artificial neural network are applied to achieve an overall accuracy of 88% for genre based classification and 73% and 67% accuracy for the arousal and valence axes respectively in mood based classification.