https://iaeme.com/Home/journal/IJEET 251 editor@iaeme.com International Journal of Electrical Engineering and Technology (IJEET) Volume 12, Issue 6, June 2021, pp. 251-258, Article ID: IJEET_12_06_024 Available online at https://iaeme.com/Home/issue/IJEET?Volume=12&Issue=6 ISSN Print: 0976-6545 and ISSN Online: 0976-6553 DOI: 10.34218/IJEET.12.6.2021.024 © IAEME Publication Scopus Indexed A NORTH INDIAN RAGA RECOGNITION USING ENSEMBLE CLASSIFIER Anagha A. Bidkar Research Scholar, Department of Electronics and Telecommunication, Vishwakarma Institute of Information Technology, And Pune Institute of Computer Technology, SPPU- Savitribai Phule Pune University, Pune, Maharashtra, India Rajkumar S. Deshpande Department of Electronics and Telecommunication, JSPM’s Imperial College of Engineering, SPPU- Savitribai Phule Pune University, Pune, Maharashtra, India Yogesh H. Dandawate Department of Electronics and Telecommunication, Vishwakarma Institute of Information Technology, SPPU- Savitribai Phule Pune University, Pune, Maharashtra, India ABSTRACT Indian classical music is an ancient art form. Western and Indian music differ in the sequence of musical notes that are present in the melodic segment. Raga recognition in Indian classical music has been an exciting area of music information retrieval system. This can be useful to create a music library, search raga related music, and music education system. Recognition of raga using machine learning algorithms is a very complex task. This paper aims to find a suitable classifier for a dataset of instrumental music of 12 ragas. The music database has audio files of 4 different musical instruments. For this dataset, the ensemble bagged tree classifier outperforms the raga recognition. This approach suits our dataset to gain accuracy of 96.32%. This paper compares the results with the ensemble subspace KNN model which gives an accuracy of 95.83%. From the derived results, it is observed that ensemble classifiers are better for variants of MFCC features extracted for our North Indian Raga Dataset. Key words: North Indian Raga, Audio Feature Extraction, (MFCC) Mel Frequency Cepstral Coefficients, Ensembel Bagged Tree, Ensemble subspace KNN Cite this Article: Anagha A. Bidkar, Rajkumar S. Deshpande, Yogesh H. Dandawate, A North Indian Raga Recognition using Ensemble Classifier, International Journal of Electrical Engineering and Technology (IJEET), 12(6), 2021, pp. 251-258. https://iaeme.com/Home/issue/IJEET?Volume=12&Issue=6