Automatic Genre Classification of Musical Signals. (2nd October 2006)

• Record Type: Journal Article
• Authors: Barbedo Barbedo, Jayme Garcia Arnal Jayme Garcia Arnal; Lopes Lopes, Amauri Amauri
• Other Names: Tzanetakis Tzanetakis George George Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2006-10-02
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/64960
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : We present a strategy to perform automatic genre classification of musical signals. The technique divides the signals into 21.3 milliseconds frames, from which 4 features are extracted. The values of each feature are treated over 1-second analysis segments. Some statistical results of the features along each analysis segment are used to determine a vector of summary features that characterizes the respective segment. Next, a classification procedure uses those vectors to differentiate between genres. The classification procedure has two main characteristics: (1) a very wide and deep taxonomy, which allows a very meticulous comparison between different genres, and (2) a wide pairwise comparison of genres, which allows emphasizing the differences between each pair of genres. The procedure points out the genre that best fits the characteristics of each segment. The final classification of the signal is given by the genre that appears more times along all signal segments. The approach has shown very good accuracy even for the lowest layers of the hierarchical structure.