Extracting significant repeating figures in music by using quantized melody contour

To extract music features from the raw data of music object and organize them as the music indices is important for music retrieval. A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is def...

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description To extract music features from the raw data of music object and organize them as the music indices is important for music retrieval. A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is defined as a melody contour of a musical segment. A sequence pattern is a melody segment that has the same figure with other melody segments. In this paper, we use the idea of interval between two adjacent notes to form quantized melody contour for representing music objects. This representation differs from existing methods that use notes to form a melody string. We also propose a method to find significant repeating figures. These figures could cover most of the repeating patterns that are in a noted melody string. In addition, the number of repeating figures found in samples of music is less than that of repeating patterns. As a result, the total execution time and memory space can be dramatically decreased.
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subjects Cities and towns
Content based retrieval
Data mining
Feature extraction
Microphones
Multimedia databases
Multiple signal classification
Music information retrieval
Query processing
Research and development
title Extracting significant repeating figures in music by using quantized melody contour
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