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Music Genre Classification Using a Time-Delay Neural Network

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

A method is proposed for classifying music genre for audio retrieval systems using time-delay neural networks. The proposed classification method considers eight types of music genre: Blues, Country, Hard Core, Hard Rock, Jazz, R&B(Soul), Techno, and Trash Metal. The melody between bars in the music is used to distinguish the different genres. The melody pattern is extracted based on the sound of a snare drum, which is used to effectively represent the rhythm periodicity. Classification is based on a time-delay neural network that uses a Fourier transformed vector of the melody as an input pattern. This classification method was used to analyze 80 training data from ten different musical pieces for each genre and a further 40 test data from five additional musical pieces for each genre. The accuracy of the genre classifications that were obtained for the two sets of data was 92.5% and 60%, respectively.

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© 2006 Springer-Verlag Berlin Heidelberg

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Lee, JW., Park, SB., Kim, SK. (2006). Music Genre Classification Using a Time-Delay Neural Network. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_27

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  • DOI: https://doi.org/10.1007/11760023_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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