利用量化的旋律轮廓提取音乐中重要的重复数字

Chuan-Wang Chang, H. C. Jiau
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引用次数: 6

摘要

从音乐对象的原始数据中提取音乐特征并将其组织成音乐索引是音乐检索的重要内容。重复模式是一系列出现不止一次的音符。大多数重复的模式是人们容易记住的主题或音调。图形被定义为音乐片段的旋律轮廓。序列模式是与其他旋律片段具有相同图形的旋律片段。本文利用相邻两个音符之间的音程思想,形成量化的旋律轮廓来表示音乐对象。这种表现方式不同于现有的用音符组成旋律的方法。我们还提出了一种寻找有效重复数字的方法。这些数字可以涵盖大多数的重复模式,在一个著名的旋律弦乐。此外,在音乐样本中发现的重复数字的数量少于重复模式的数量。因此,总执行时间和内存空间可以显著减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 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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