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Efficient Repeating Segments Discovery in Music using Adaptive Motif Generation Algorithm
Title: | Efficient Repeating Segments Discovery in Music using Adaptive Motif Generation Algorithm |
Authors: | Wang, Lei Browse this author | Chng, Eng Siong Browse this author | Li, Haizhou Browse this author |
Issue Date: | 4-Oct-2009 |
Publisher: | Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee |
Journal Title: | Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference |
Start Page: | 895 |
End Page: | 903 |
Abstract: | This paper introduces an efficient unsupervised algorithm to discover motifs in multivariate data sequence. Specifically, we apply our proposed work to detect repeating segments on music feature vectors. The proposed algorithm, namely Adaptive Motif Generation, scans the music features online to construct a list of repeating candidate segments in linear time. The candidate list is then used to populate a sparse self-similarity matrix for further processing to generate the final selections. The experimental results showed that the proposed approach was able to obtain similar average F1 score compared to the traditional self-similarity approach with significant reduction in computational cost and memory usage. |
Description: | APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Oral session: Multimedia Analysis and Processing (7 October 2009). |
Conference Name: | APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference | 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 |
Conference Place: | Sapporo |
Type: | proceedings |
URI: | http://hdl.handle.net/2115/39829 |
Appears in Collections: | 北海道大学サステナビリティ・ウィーク2009 (Sustainability Weeks 2009) > 2009年アジア太平洋信号情報処理連合学会アニュアルサミット・国際会議 (2009 APSIPA Annual Summit and Conference)
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