Fault Tolerant Non-trivial Repeating Pattern Discovering for Music Data

  • Authors:
  • Yu-lung Lo;Chun-yu Chen

  • Affiliations:
  • Chaoyang University of Technology;Chaoyang University of Technology

  • Venue:
  • ICIS-COMSAR '06 Proceedings of the 5th IEEE/ACIS International Conference on Computer and Information Science and 1st IEEE/ACIS International Workshop on Component-Based Software Engineering,Software Architecture and Reuse
  • Year:
  • 2006

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Abstract

A non-trivial repeating pattern is commonly used in analyzing the repeated part of a music object and looking for the theme. Non-trivial repeating patterns exclude those patterns included in other longer patterns such that they can reduce the redundancy and speedup music search. So far, existing approaches discover a repeating pattern in such a way that the sequence of notes in a music object appears more than once in exactly matching. If we allow the similar sequences with partial different notes also being a repeating pattern, it can reduce the number of repeating patterns and construct more efficient music indexes. The more accurate music theme also could be analyzed. Therefore, in this paper, we propose a faulttolerant non-trivial repeating pattern discovering technique. The experimental results show that our approach can not only reduce the number of nontrivial repeating patterns but also improve the hit ratios of queries for music databases.