A Comparison of Identification Methods of Brazilian Music Styles by Lyrics

Patrick Guimarães, Jader Froes, Douglas Costa, Larissa Freitas


Abstract
In our work, we applied different techniques for the task of genre classification using lyrics. Utilizing our dataset with lyrics of typical genres in Brazil divided into seven classes, we apply some models used in machine learning and deep learning classification tasks. We explore the performance of usual models for text classification using an input in the Portuguese language. We also compare the use of RNN and classic machine learning approaches for text classification, exploring the most used methods in the field.
Anthology ID:
2020.winlp-1.16
Volume:
Proceedings of the Fourth Widening Natural Language Processing Workshop
Month:
July
Year:
2020
Address:
Seattle, USA
Editors:
Rossana Cunha, Samira Shaikh, Erika Varis, Ryan Georgi, Alicia Tsai, Antonios Anastasopoulos, Khyathi Raghavi Chandu
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
61–63
Language:
URL:
https://aclanthology.org/2020.winlp-1.16
DOI:
10.18653/v1/2020.winlp-1.16
Bibkey:
Cite (ACL):
Patrick Guimarães, Jader Froes, Douglas Costa, and Larissa Freitas. 2020. A Comparison of Identification Methods of Brazilian Music Styles by Lyrics. In Proceedings of the Fourth Widening Natural Language Processing Workshop, pages 61–63, Seattle, USA. Association for Computational Linguistics.
Cite (Informal):
A Comparison of Identification Methods of Brazilian Music Styles by Lyrics (Guimarães et al., WiNLP 2020)
Copy Citation:
Video:
 http://slideslive.com/38929552