Abstract
Genre-based classification of song is one of the major steps in the music retrieval system. In this work, we have presented perception-based song genre classification. Many of the past researchers have been using combination of perception-based features and other popular features such as zero-crossing, short-time energy. We have used three perceptual features that capture the ordering of sound in frequency scale (pitch-based features), the pace of a musical piece (tempo-based features), and repetition of a pattern in the audio signal. In order to capture the repeating pattern in a signal, we have used cooccurrence matrix. The experimental result using multilayer perceptron network as a classifier indicates the effectiveness of our proposed scheme.
Keywords
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Ghosal, A., Chakraborty, R., Dhara, B.C., Saha, S.K. (2014). Genre-Based Classification of Song Using Perceptual Features. In: Mohapatra, D.P., Patnaik, S. (eds) Intelligent Computing, Networking, and Informatics. Advances in Intelligent Systems and Computing, vol 243. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1665-0_26
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DOI: https://doi.org/10.1007/978-81-322-1665-0_26
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