Abstract
Tabla is the most common rhythmic instrument in Indian Classical music. A bol the fundamental unit of tabla play and it is produced by striking either or both of the two drums of tabla. Tala (rhythm) is formed with a basic sequence of bols that appears in a cyclic pattern. In this work, bols are automatically segmented from tabla signal following Attack-Decay-Sustain-Release (ADSR) model. Subsequently segmented bols are recognized using low level spectral descriptors and support vector machine (SVM). The identified bol sequence generates transcript of tabla play. A template based matching approach is used to identify tala from the transcript. Proposed system tested successfully with a variety of collection of tabla signal of different talas and it can be utilized in rhythm analysis of music. Moreover, for the learners also the system can help in analyzing their performance.
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Sarkar, R., Mondal, A., Singh, A., Saha, S.K. (2018). Automatic Identification of Tala from Tabla Signal. In: Gavrilova, M., Tan, C., Chaki, N., Saeed, K. (eds) Transactions on Computational Science XXXI. Lecture Notes in Computer Science(), vol 10730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-56499-8_2
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DOI: https://doi.org/10.1007/978-3-662-56499-8_2
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