Rhythm and timbre analysis for carnatic music processing

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Abstract

In this work, an effort has been made to analyze rhythm and timbre related features to identify raga and tala from a piece of Carnatic music. Raga and Tala classification is performed using both rhythm and timbre features. Rhythm patterns and rhythm histogram are used as rhythm features. Zero crossing rate (ZCR), centroid, spectral roll-off, flux, entropy are used as timbre features. Music clips contain both instrumental and vocals. To find similarity between the feature vectors T-Test is used as a similarity measure. Further, classification is done using Gaussian Mixture Models (GMM). The results shows that the rhythm patterns are able to distinguish different ragas and talas with an average accuracy of 89.98 and 86.67 % respectively.

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APA

Heshi, R., Suma, S. M., Koolagudi, S. G., Bhandari, S., & Rao, K. S. (2016). Rhythm and timbre analysis for carnatic music processing. In Smart Innovation, Systems and Technologies (Vol. 43, pp. 603–609). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-81-322-2538-6_62

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