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Melodic pattern recognition in Indian classical music for raga identification

机译:印度古典音乐中的旋律模式识别为raga识别

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Melody is the soul of the Indian classical music for raga identification. This paper evaluates different algorithms proposed for raga recognition for effectiveness and computational cost. As per the analysis done, the pitch class distribution and N-gram approaches found out to be more effective. It was revealed that none of the research focused on the facet of minimum duration sample required for identification. The main aim of the experiments is to identify the least duration sample required for identification of raga. Least duration will lead to less computational cost and time. Dataset used is voiced audio samples of monophonic music with duration of audio samples ranging from 30 to 180 s from the beginning of raga rendition. Pitch extraction for melodic data is done using auto correlation method in tool praat. Findings revealed that different ragas require varied duration for accurate identification. Potential directions to improve the raga identification performance with less possible duration are proposed.
机译:旋律是印度古典音乐的灵魂,为raga识别。本文评估了提出的不同算法,为raga识别进行有效性和计算成本。根据所做的分析,发现俯仰类分布和N-GRAM方法更有效。据透露,没有一项研究集中在鉴定所需的最小持续时间样本的方面。实验的主要目的是鉴定鉴定raga所需的最小持续时间样本。最小持续时间将导致计算成本和时间较少。使用的数据集是声音音乐的音频样本,其音频样本的持续时间范围为raga rendition的开头的30到180秒。使用工具PRAAT中的自动相关方法完成旋转旋转曲调。调查结果显示,不同的ragas需要各种持续时间以准确识别。提出了提高持续可能持续时间较少的raga识别性能的潜在方向。

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