In recent years, the music has become popular due to the evolution of the technology. Various kinds of music around us become complexities and huge. The explosive
growth in the music has generated the urgent need for new techniques and tools
that can intelligently and automatically transform the music into useful information.
Many researches consider the music object as an continuously discrete note in time
order. Repeating patterns are some subsequences which appear frequently in the
music sequence. The repeating patterns usually can represent the theme of a music
object. Moreover, it also can be utilized in music classification. Many methods have
been proposed for finding the repeating patterns in music objects, for example, the
M2P (Mining Maximum-length Patterns) method. It constructs a directed graph and
uses the depth-first search to traverse the graph. It calculates the paths by the string
matching algorithm to decide whether they are repeating pattern, and finds out the
maximum-length repeating pattern in a music sequence. Although the M2P method
is a straightforward method to find out the patterns, it consumes time in creating too
many candidate patterns and performing the string matching algorithm. Therefore,
in this thesis, we propose the PJ (Position-Join) method to efficiently find out the
maximum-length repeating pattern. In the constructing graph step, we find out that
we can modify the information in the graph, and avoid to use the string matching
algorithm to decide whether a path is repeating pattern. We record the positions of
length two repeating patterns in the matrix. While traversing the graph, we calculate the frequency by the information of positions. Moreover, we record the repeated
path by the positions. We create terminal edges, and record the information of paths
which have been traversed. We dynamically modify the graph by terminal edges. It
can avoid to traverse some paths repeatedly in traversing the graph step. From our
performance study based on the synthetic data and real music data, we show that
our proposed PJ method is more efficient than the M2P method.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0712111-140138 |
| Date | 12 July 2011 |
| Creators | Chen, Tien-hsiu |
| Contributors | Ye-In Chang, Chien-I Lee, Shian-Hua Lin, Gen-Huey Chen |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0712111-140138 |
| Rights | withheld, Copyright information available at source archive |
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