Modelo automático de classificação de gêneros musicais amazônicos
Abstract
Globalization affects the musical preference of today’s society, which has continued esteemed by international rhythms compared to the national or local. Music is a form of communication used for the construction and organization of the social structure, which It influences lifestyles, tastes, and interpersonal relationships. Therefore, each musical genre manifestation has different functions for a listener, for example, to dance, celebrate, rest, help in solitude, sadness, etc. Several applications use music genre classifiers to indicate, preview, or suggest new music for their listeners. For various reasons, most classifiers do not have information on regional music genres. This work proposes an automatic classification model for Amazonian popular musical genres. Initially, a database was created containing the musical genres: andino, brega, carimb´o, c´umbia, marabaixo, pasillo, salsa e vaqueirada, from the Legal Amazon region of the countries: Brazil, French Guiana, Venezuela, Colombia, Ecuador, Bolivia and Peru. For the construction of the database, several characteristics of each song were extracted from a total of 64 parameters. Machine learning models were analyzed in which XGB, KNN, SVM e MLP obtained an accuracy of 67.62%, 74.12%, 71.35%, 76.13%, respectively.
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