Autor(es): Malheiro, Ricardo ; Panda, Renato ; Gomes, Paulo J. S. ; Paiva, Rui Pedro
Data: 2016
Identificador Persistente: https://hdl.handle.net/10316/95162
Origem: Estudo Geral - Universidade de Coimbra
Assunto(s): bimodal analysis; music emotion recognition
This research addresses the role of audio and lyrics in the music emo- tion recognition. Each dimension (e.g., audio) was separately studied, as well as in a context of bimodal analysis. We perform classification by quadrant catego- ries (4 classes). Our approach is based on several audio and lyrics state-of-the-art features, as well as novel lyric features. To evaluate our approach we create a ground-truth dataset. The main conclusions show that unlike most of the similar works, lyrics performed better than audio. This suggests the importance of the new proposed lyric features and that bimodal analysis is always better than each dimension.
This work was supported by CISUC (Center for Informatics and Systems of the University of Coimbra).
