Automated Transcription for Raga Recognition and Classification in Indian Classical Music Using Machine Learning

DOI

10.2991/ahis.k.210913.026How to use a DOI?

Keywords

Automate, Automatic Raga recognition, Carnatic and Hindustani Music, Indian Classical Music, Machine learning techniques, Note transcription

Abstract

Raga recognition is only possible by trained musician to understand the notes based on the lead voice but a beginner is unable to decode the notes. This is significant for current scenarios in developing an automated note transcription system in Indian Classical Music (ICM). In the present research, various properties of raga and the machine learning techniques that are used for identifying the raga by a machine rather than a human or music expert are surveyed. The previously developed automatic raga recognition techniques using Carnatic and Hindustani Music, the main drawbacks and the improvements required are discussed. The present research work discusses about the future proposed models for automatic raga recognition using pitch detection algorithm, finding Tuning Offset, and Note Segmentation process. The proposed model will obtain better accuracy more than 96 % when compared to the existing CNN, GMM that obtained accuracy of 94 % and 95 %.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - B S Gowrishankar
AU  - U Bhajantri Nagappa
PY  - 2021
DA  - 2021/09/13
TI  - Automated Transcription for Raga Recognition and Classification in Indian Classical Music Using Machine Learning
BT  - Proceedings of the 3rd International Conference on Integrated Intelligent Computing Communication & Security (ICIIC 2021)
PB  - Atlantis Press
SP  - 211
EP  - 217
SN  - 2589-4900
UR  - https://doi.org/10.2991/ahis.k.210913.026
DO  - 10.2991/ahis.k.210913.026
ID  - Gowrishankar2021
ER  -