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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/76033

    Title: Music Matching Based on Rough Longest Common Subsequence
    Authors: Lin, Hwei-Jen;Wu, Hung-Hsuan;Wang, Chun-Wei
    Contributors: 淡江大學資訊工程學系
    Keywords: content-based music retrieval;rough longest common subsequence;RLCS;local alignment;information retrieval;musical similarity;filtering algorithm
    Date: 2011-01-01
    Issue Date: 2012-04-30 17:50:31 (UTC+8)
    Publisher: Taipei: Institute of Information Science
    Abstract: In this paper we proposed a music matching method, called the RLCS(rough longest common subsequence) method. It is an impoved version of the LCS to avoid some problems occurring in global alignment matching. First a rough equality for two notes is defined for constructing the RLCS of two music fragments. The length of the RLCS of two music sequences defined in this work is a real number, called a weighted length. It is evaluated according to degree of similarity of every pair of matched notes from the two sequences. This method takes into account both the width-across-query(WAQ) and the width-across-reference(WAR) and combines them with the weighted length of the corresponding RLCS to define a score measurement for the RLCS. The measurement associated with WAQ and WAR enables the proposed method to tolerate dense errors. A dynamic programming algorithm is presented for simultaneously calculating the weighted length of RLCS, the WAQ, the WAR, and the score to determine the RLCS. As a result, the proposed method can perform the matching in a better and simplermanner. In order to speed up the matching process, we use the filter algorithm proposed by Tarhio and Ukkonen [22] to filter the reference and discard most off the reference areas that do not match. We applied the proposed algorithm to content-based music retrieval. The experimental results showed that with our proposed algorithm the retrieval system provides a higher retrieval rate than that with the local alignment method proposed by Suyoto et al. [20]. The use of filtering algorithm has been shown to greatly reduce the computation time for exact matching and for approximate matching with a low error tolerance.
    Relation: Journal of Information Science and Engineering 27(1), pp.95-110
    Appears in Collections:[資訊工程學系暨研究所] 期刊論文

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