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English Information

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Authors
# Name
1 Italo Trindade(italolt10@gmail.com)
2 Leandro Resendo(jefferson.andrade@ifes.edu.br)
3 Jefferson Andrade(jefferson.andrade@ifes.edu.br)
4 Karin Komati(kkomati@ifes.edu.br)

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Reference
# Reference
1 Araujo, C., Cristo, M., and Giusti, R. (2019). Predicting music popularity on streaming platforms. In Anais do XVII Simpósio Brasileiro de Computação Musical, pages 141–148, Porto Alegre, RS, Brasil. SBC.
2 da Silva, A. C. M., Silva, D. F., and Marcacini, R. M. (2020). 4mula - a multitask, multimodal, and multilingual dataset of music lyrics and audio features. In Anais do XXVI Simpósio Brasileiro de Multimídia e Web, pages 305–308, Porto Alegre, RS, Brasil. SBC.
3 de Araujo Lima, R., de Sousa, R. C. C., Lopes, H., and Barbosa, S. D. J. (2020). Brazilian lyrics-based music genre classification using a BLSTM network. In International Conference on Artificial Intelligence and Soft Computing, pages 525–534. Springer.
4 de Melo Faria, F. L., Pereira Jr, A. R., and Merschmann, L. H. (2015). Prediction of artists’ rankings by regression. In SBSI, pages 95–102.
5 Pereira, P. G. (2015). As relações entre língua, cultura, música e o processo de ensino-aprendizagem de língua estrangeira. Revista Estudos Anglo-Americanos, (43):62–83.
6 Powell-Morse, A. (2015). Lyric intelligence in popular music: A ten year analysis. https://www.seatsmart.com/blog/lyric-intelligence/.
7 Ribeiro, R. and Silla, C. (2014). Recuperação inteligente de letras de músicas na web. In: Anais do XXXIII Concurso de Trabalhos de Iniciação Científica da SBC, pages 41–50. SBC.
8 Schedl, M., Gomez, E., and Urbano, J. (2014). Music information retrieval: Recent developments and applications. Foundations and Trends in Information Retrieval, 8:127–261.
9 Silva, M. O., de Alencar Rocha, L. M., and Moro, M. M. (2019). MusicOSet: An enhanced open dataset for music data mining. In XXXII Simpósio Brasileiro de Banco de Dados: Dataset Showcase Workshop, SBBD 2019 Companion, Fortaleza, CE, Brazil. SBC.
10 Solnyshkina, M., Zamaletdinov, R., Gorodetskaya, L., and Gabitov, A. (2017). Evaluating text complexity and flesch-kincaid grade level. Journal of Social Studies Education Research, 8(3):238–248.