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Nowadays is common to have the music stored using some digital format. However, because the large amount of data, it is impossible to make an accurate classification of all existing music without some kind of software. Attending to this requirement, in this work we developed a musical genres using a segmentation process together with some spectral characteristics such as centroid (SC), flatness (SF) and spread (SS) as well as temporary characteristic

Algoritmos de aprendizaje supervisado para la clasificación de géneros musicales caracterizados mediante modelos estadísticos