Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/95162
Title: Bi-Modal Music Emotion Recognition: Novel Lyrical Features and Dataset
Authors: Malheiro, Ricardo 
Panda, Renato 
Gomes, Paulo J. S. 
Paiva, Rui Pedro 
Keywords: bimodal analysis; music emotion recognition
Issue Date: 2016
Serial title, monograph or event: 9th International Workshop on Music and Machine Learning – MML 2016 – in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECML/PKDD 2016
Place of publication or event: Riva del Garda, Italy
Abstract: 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.
URI: http://hdl.handle.net/10316/95162
Rights: openAccess
Appears in Collections:I&D CISUC - Artigos em Livros de Actas

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