Song emotion recognition using music genre information

Abstract

Music Emotion Recognition (MER) is an important topic in music understanding, recommendation and retrieval that has gained great attention in the last years due to the constantly increasing number of people accessing digital musical content. In this paper we propose a new song emotion recognition system that takes into consideration the song’s genre and we investigate the effect that genre has, on the recognition task of four basic music emotions of the valence-arousal (VA) plane: happy, angry, sad and peaceful. Experiments on a database consisting of 1100 songs from four different music genres (blues, country, pop and rock) using timbral, spectral, dynamical and chroma descriptors of the music, have shown that successful recognition of the song’s genre as a pre-processing step, can improve the recognition of its emotion by a factor of 10–15%.