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Automatic Tonic (Shruti) Identification System for Indian Classical Music

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Soft Computing and Signal Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 900))

Abstract

In Indian classical music, identification of basic pitch is a crucial task to explore information of full raga. Here recorded dataset of both instrumental and vocal raga excerpts is used. Pitch frequency is calculated using subharmonic-to-harmonic ratio. Pitch estimation using SHR is tested for nine different instruments, and it shows 95.06% pitch detection accuracy which is better compared to other methods. Each frame of the raga is processed to increase efficiency in the tonic identification. Pitch histogram is used to extract various features of the raga. The various machine learning algorithms are tested, and the best algorithm is used to find set of rules for the evaluation of Tonic. The very famous J48 decision-tree algorithm shows highest test accuracy of 92.86% for tonic identification. This test model is further used to build an iterative system for tonic identification with the highest confidence. The proposed system is tested for two datasets. Tonic identification accuracy for the first dataset is 90.5%, and it is 93.05% for the second dataset.

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Authors and Affiliations

  1. College of Engineering, Pune, 411005, India

    Mahesh Y. Pawar & Shrinivas Mahajan

Authors
  1. Mahesh Y. Pawar
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  2. Shrinivas Mahajan
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Corresponding author

Correspondence to Mahesh Y. Pawar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Software Engineering, Monmouth University, West Long Branch, NJ, USA

    Jiacun Wang

  2. Department of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangaluru, Karnataka, India

    G. Ram Mohana Reddy

  3. Department of Computer Science and Engineering, JNTUH College of Engineering Hyderabad, Hyderabad, Telangana, India

    V. Kamakshi Prasad

  4. Department of Electronics and Communication Engineering, Malla Reddy College of Engineering and Technology, Secunderabad, Telangana, India

    V. Sivakumar Reddy

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Pawar, M.Y., Mahajan, S. (2019). Automatic Tonic (Shruti) Identification System for Indian Classical Music. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 900. Springer, Singapore. https://doi.org/10.1007/978-981-13-3600-3_70

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