Please use this identifier to cite or link to this item:

Title: Discovering nontrivial repeating patterns in music data
Authors: 陳良弼
Hsu,Jia-Lien;Liu,Chih-Chin;Chen,Arbee L.P.
Contributors: 資科系
Date: 2001-09
Issue Date: 2014-08-21 15:09:05 (UTC+8)
Abstract: A repeating pattern in music data is defined as a sequence of notes which appears more than once in a music object. The themes are a typical kind of repeating patterns. The themes and other nontrivial repeating patterns are important music features which can be used for both content-based retrieval of music data and music data analysis. In this paper, we propose two approaches for fast discovering nontrivial repeating patterns in music objects. In the first approach, we develop a data structure called correlative matrix and its associated algorithms for extracting the repeating patterns. In the second approach, we introduce a string-join operation and a data structure called RP-tree for the same purpose. Experiments are performed to compare these two approaches with others. The results are further analyzed to show the efficiency and the effectiveness of our approaches
Relation: IEEE Transactions on Multimedia (EI,SCIE),3(3),311-325
Data Type: article
Appears in Collections:[資訊科學系] 期刊論文

Files in This Item:

File Description SizeFormat

All items in 學術集成 are protected by copyright, with all rights reserved.

社群 sharing