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Research Article | Open Access |

Automatic Melakarta Raaga Identification Syste: Carnatic Music

Author 1: B Tarakeswara Rao Author 2: Sivakoteswararao Chinnam Author 3: P Lakshmi Kanth Author 4: M.Gargi
International Journal of Advanced Research in Artificial Intelligence (IJARAI) · Vol. 1, No. 4 · Published 2012 · Cited by 8

DOI: 10.14569/IJARAI.2012.010406

Abstract

It is through experience one could as certain that the classifier in the arsenal or machine learning technique is the Nearest Neighbour Classifier. Automatic melakarta raaga identification system is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance today because issues of poor run-time performance are not such a problem these days with the computational power that is available. This paper presents an overview of techniques for Nearest Neighbour classification focusing on; mechanisms for finding distance between neighbours using Cosine Distance, Earth Movers Distance and formulas are used to identify nearest neighbours, algorithm for classification in training and testing for identifying Melakarta raagas in Carnatic music. From the derived results it is concluded that Earth Movers Distance is producing better results than Cosine Distance measure.

Keywords

How to Cite this Article

Rao, B. T., Chinnam, S., Kanth, P. L., & M.Gargi (2012). Automatic Melakarta Raaga Identification Syste: Carnatic Music. International Journal of Advanced Research in Artificial Intelligence, 1(4). https://doi.org/10.14569/IJARAI.2012.010406

Rao, B Tarakeswara, et al.. "Automatic Melakarta Raaga Identification Syste: Carnatic Music." International Journal of Advanced Research in Artificial Intelligence, vol. 1, no. 4, 2012, https://doi.org/10.14569/IJARAI.2012.010406.

@article{Rao2012,
  title     = {Automatic Melakarta Raaga Identification Syste: Carnatic Music},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {1},
  number    = {4},
  year      = {2012},
  publisher = {The Science and Information Organization},
  author    = {B Tarakeswara Rao and Sivakoteswararao Chinnam and P Lakshmi Kanth and M.Gargi},
  doi       = {10.14569/IJARAI.2012.010406},
  url       = {https://doi.org/10.14569/IJARAI.2012.010406}
}

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