Music Genre Classification Based on Paraconsistency
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Data
2015-01-01
Autores
Silva Paulo, Katia Cristina
Solgon Bassi, Regiane Denise
Delorme, Andre Luis
Guido, Rodrigo Capobianco [UNESP]
Silva, Ivan Nunes da
Anonymous
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Editor
Destech Publications, Inc
Resumo
This work aims to build an intelligent system for Music Genre Classification (MGC) based on Para-consistent Annotated Logic (LPA). Using a database composed of representative samples of songs from different styles, namely jazz, bolero, bossa nova, forro, salsa, and swing, as well as a paraconsistent discriminative classifier, a supervised approach was developed to solve the problem. Particularly, the proposed system does not necessarily match songs and genres definitely. Instead, it quantifies the degree of similarity between them.
Descrição
Palavras-chave
Music genre classification, Artificial intelligence, Paraconsistent discriminating Machine (DPM), paraconsistency
Como citar
2nd International Conference On Advanced Education Technology And Management Science (aetms 2014). Lancaster: Destech Publications, Inc, p. 427-431, 2015.