Brazilian Lyrics-Based Music Genre Classification Using a BLSTM Network
- URL: http://arxiv.org/abs/2003.05377v1
- Date: Fri, 6 Mar 2020 05:39:21 GMT
- Title: Brazilian Lyrics-Based Music Genre Classification Using a BLSTM Network
- Authors: Raul de Ara\'ujo Lima, R\^omulo C\'esar Costa de Sousa, Simone Diniz
Junqueira Barbosa, H\'elio Cort\^es Vieira Lopes
- Abstract summary: We present a novel approach for automatic classifying musical genre in Brazilian music using only the song lyrics.
We construct a dataset of 138,368 Brazilian song lyrics distributed in 14 genres.
Some genres like "gospel", "funk-carioca" and "sertanejo" can be defined as the most distinct and easy to classify.
- Score: 1.9116784879310027
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Organize songs, albums, and artists in groups with shared similarity could be
done with the help of genre labels. In this paper, we present a novel approach
for automatic classifying musical genre in Brazilian music using only the song
lyrics. This kind of classification remains a challenge in the field of Natural
Language Processing. We construct a dataset of 138,368 Brazilian song lyrics
distributed in 14 genres. We apply SVM, Random Forest and a Bidirectional Long
Short-Term Memory (BLSTM) network combined with different word embeddings
techniques to address this classification task. Our experiments show that the
BLSTM method outperforms the other models with an F1-score average of $0.48$.
Some genres like "gospel", "funk-carioca" and "sertanejo", which obtained 0.89,
0.70 and 0.69 of F1-score, respectively, can be defined as the most distinct
and easy to classify in the Brazilian musical genres context.
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