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25 October 2004 Music genre classification using temporal domain features
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Proceedings Volume 5601, Internet Multimedia Management Systems V; (2004) https://doi.org/10.1117/12.571369
Event: Optics East, 2004, Philadelphia, Pennsylvania, United States
Abstract
Music genre provides an efficient way to index songs in the music database, and can be used as an effective means to retrieval music of a similar type, i.e. content-based music retrieval. In addition to other features, the temporal domain features of a music signal are exploited so as to increase the classification rate in this research. Three temporal techniques are examined in depth. First, the hidden Markov model (HMM) is used to emulate the time-varying properties of music signals. Second, to further increase the classification rate, we propose another feature set that focuses on the residual part of music signals. Third, the overall classification rate is enhanced by classifying smaller segments from a test material individually and making decision via majority voting. Experimental results are given to demonstrate the performance of the proposed techniques.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yu Shiu and C.-C. Jay Kuo "Music genre classification using temporal domain features", Proc. SPIE 5601, Internet Multimedia Management Systems V, (25 October 2004); https://doi.org/10.1117/12.571369
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