卡纳蒂克音乐中联合拉格舞曲的鉴定

Prithvi Upadhyaya, M. SumaS., S. Koolagudi
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引用次数: 1

摘要

在这部作品中,人们努力区分卡纳蒂克音乐中的联合拉格。联合拉格是使用相同音符组合而成的拉格。从音高序列中得到的特征被用来区分这些拉格。用来拟合歌曲片段的音高轮廓的勒让德多项式系数用于识别拉格。使用神经网络、朴素贝叶斯、多类分类器、Bagging和随机森林等不同的分类器对得到的特征进行验证。所提出的系统在4组联合raagas上进行了测试。朴素贝叶斯分类器对Todi-Dhanyasi的联合集的平均准确率为86.67%,多类分类器对Kharaharapriya-Anandabhairavi-Reethigoula的联合集的平均准确率为86.67%。一般来说,神经网络分类器的性能优于其他分类器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of allied raagas in Carnatic music
In this work, an effort has been made to differentiate the allied raagas in Carnatic music. Allied raagas are the raagas that are composed using same set of notes. The features derived from the pitch sequence are used for differentiating these raagas. The coefficients of legendre polynomials, used to fit the pitch contours of the song clips are used for identifying raagas. Obtained features are validated using different classifiers such as Neural networks, Naive Bayes, Multi class classifier, Bagging and Random forest. The proposed system is tested on 4 sets of allied raagas. Naive Bayes classifier gives an average accuracy of 86.67% for allied set of Todi-Dhanyasi and Multi class classifier gives an average accuracy of 86.67% for allied set of Kharaharapriya-Anandabhairavi-Reethigoula. In general, Neural network classifier performance is found to be better than other classifiers.
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