Rock Genre Classification Using K-Nearest Neighbor

Yoppy Sazaki

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Abstract

Music genre classification is a part of Music Information Retrieval. This research was a genre music detection based on signal from an audio. Divided into two processes namely extraction of features and classification. Signal would be transformed using Fast Fourier Transform to get frequency domain signal which will be processed to extract Short Time Energy, Spectral Centroid, Spectral Roll-Off, Spectral Flux, and Energy Entropy feature. Besides those features, Zero Crossing Rate would be counted from time-domain signal. in classifying phase, research using k nearest neighbor with accuracy reaching 54,44%.

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Conference

1st International Conference on Computer Science and Engineering

  • Konferensi di Palembang, Indonésia pada tahun 2014
  • 28 articles

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