基于自组织映射的印度古典音乐拉格聚类分析方法

Akhilesh K. Sharma, Kamaljit I. Lakhtaria, A. Panwar, S. Vishwakarma
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引用次数: 11

摘要

本文主要研究了拉格识别中的自组织映射,以及拉格识别和聚类的数字信号处理策略。本文主要描述了SOM输入的所有特征提取机制,并设计了一种基于PCP(音高类轮廓)和检测到的起跳来创建拉格的聚类的算法。我们的策略很有前途,它提供了更好的拉格模式集群,拉格片段与其他拉格明显不同,因为我们比较了它们的关键属性。印度古典音乐史非常古老根据拉格的起首来识别音乐的需求对音乐专业人士和国内用户来说非常有帮助,他们可以在没有任何专家帮助的情况下识别和检测拉格的类型并使用它。因此,我们的策略在本质上是非常有前途的新手用户和从业者以及家庭用户。非常早期的学习者也会发现它非常有趣和支持适当的时间后,经常使用它。最后,我们提供了增强功能的未来可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Analytical approach based on self organized maps (SOM) in Indian classical music raga clustering
This paper is mainly focusing the aspects regarding the Self organized maps in the recognition of the Ragas and the strategy behind the Digital signal processing for the raga recognition and clustering of the same. Paper mainly describes all the features extraction mechanism for the SOM input and we devised an algorithm for creating the clusters of the raga based on their PCP (pitch class profiles) and the onsets detected. Our strategy is very promising that its providing better clusters of the raga patterns and the raga segments are very much clearly be distinguished from the other ragas, as we compared them with the formation of the key attributes. The Indian classical music history is very old and the need for identifying the music based on the raga onsets is very much helping for the music professionals and domestic users for identifying and detecting the raga types and using the same without the help or availability of any experts nearby. Thus our strategy is very promising in nature for the novice users and practitioners as well as home users. The very early learners would also find it very interesting and supportive after due course of frequent uses of it. At last we provided the future possibilities for the enhancements.
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