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Forroset: A Multipurpose Dataset of Brazilian Forró Music

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Advances in Artificial Intelligence – IBERAMIA 2022 (IBERAMIA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13788))

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Abstract

Forró is an important genre that has been developing the cultural identity of Brazil and it is one of the most consumed by Brazilians on Spotify. However, the lack of datasets and their specificity leads to less research about this genre. In order to overcome this issue, it is presented a set of data roughly compounded by 3000 songs named Forroset, which provides editorial information, audio features, information of rhythm, and audio files from Spotify. Furthermore, over 1400 lyrics of songs were obtained by the Vagalume platform. When Forroset is compared to other sets of data, it was seen that our dataset is more powerful regarding the diversity of information heading to comprehensive problems resolution.

Supported by CAPES. Financing code 001 and Fellowship 88887.517813/2020-00.

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Notes

  1. 1.

    https://www.forroemvinil.com/.

  2. 2.

    https://developer.spotify.com/documentation/web-api/.

  3. 3.

    https://spotipy.readthedocs.io/en/2.19.0/.

  4. 4.

    https://librosa.org/doc/latest/index.html.

  5. 5.

    https://api.vagalume.com.br/.

  6. 6.

    https://github.com/diegoteixeir4/python-vagalume.

  7. 7.

    https://docs.python.org/3/library/difflib.html.

  8. 8.

    https://developer.spotify.com/terms/.

  9. 9.

    https://www.go-fair.org/fair-principles/.

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Author information

Authors and Affiliations

  1. Programa de Pós-Graduação em Ciência da Computação, Departamento de Informática, Universidade Federal de Viçosa, Viçosa, Brazil

    Lucas Ferreira-Paiva

  2. Programa de Pós-Graduação em Bioinformática, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Elizabeth Regina Alfaro-Espinoza

  3. Departamento de Engenharia Elétrica, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil

    Pablo de Souza Vieira Santana, Amanda Bomfim Moitinho, Leonardo Bonato Felix & Rodolpho Vilela Alves Neves

  4. Centro de Ciências Exatas e Tecnológicas - Engenharia de Computação, Centro Universitário de Viçosa, Viçosa, Brazil

    Vinicius Martins Almeida

Authors
  1. Lucas Ferreira-Paiva
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  2. Elizabeth Regina Alfaro-Espinoza
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  3. Pablo de Souza Vieira Santana
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  4. Vinicius Martins Almeida
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  5. Amanda Bomfim Moitinho
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  6. Leonardo Bonato Felix
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  7. Rodolpho Vilela Alves Neves
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Corresponding author

Correspondence to Lucas Ferreira-Paiva .

Editor information

Editors and Affiliations

  1. Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Ana Cristina Bicharra Garcia

  2. Fluminense Federal University, Niterói, Brazil

    Mariza Ferro

  3. University of Cartagena, Cartagena de Indias, Colombia

    Julio Cesar Rodríguez Ribón

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Ferreira-Paiva, L. et al. (2022). Forroset: A Multipurpose Dataset of Brazilian Forró Music. In: Bicharra Garcia, A.C., Ferro, M., Rodríguez Ribón, J.C. (eds) Advances in Artificial Intelligence – IBERAMIA 2022. IBERAMIA 2022. Lecture Notes in Computer Science(), vol 13788. Springer, Cham. https://doi.org/10.1007/978-3-031-22419-5_2

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  • DOI: https://doi.org/10.1007/978-3-031-22419-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22418-8

  • Online ISBN: 978-3-031-22419-5

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