Silva Paulo, Katia CristinaSolgon Bassi, Regiane DeniseDelorme, Andre LuisGuido, Rodrigo Capobianco [UNESP]Silva, Ivan Nunes daAnonymous2018-11-262018-11-262015-01-012nd International Conference On Advanced Education Technology And Management Science (aetms 2014). Lancaster: Destech Publications, Inc, p. 427-431, 2015.http://hdl.handle.net/11449/164854This 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.427-431engMusic genre classificationArtificial intelligenceParaconsistent discriminating Machine (DPM)paraconsistencyTrabalho apresentado em eventoWOS:000352704700082Acesso aberto65420862268080670000-0002-0924-8024