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2020 | OriginalPaper | Chapter

Automatic Classification of Carnatic Music Instruments Using MFCC and LPC

Authors : Surendra Shetty, Sarika Hegde

Published in: Data Management, Analytics and Innovation

Publisher: Springer Singapore

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Abstract

With a large collection of digital music in recent days, the challenge is to organize and access the music efficiently. Research in the field of Music Information Retrieval (MIR) focuses on these challenges. In this paper, we develop a system which automatically identifies the instrument in a given Carnatic music on ten different types of instruments. We extract the well-known features namely, MFCC and LPC, and analyze the capability of these features in distinguishing different instruments. Then, we apply, the classification techniques like, Artificial Neural Network, Support Vector Machine, and Bayesian classifiers on those features. We compare the performances of those algorithms along with different features for Carnatic music instruments identification.

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Metadata
Title
Automatic Classification of Carnatic Music Instruments Using MFCC and LPC
Authors
Surendra Shetty
Sarika Hegde
Copyright Year
2020
Publisher
Springer Singapore
Book
Data Management, Analytics and Innovation

Print ISBN: 978-981-329-948-1

Electronic ISBN: 978-981-329-949-8

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-32-9949-8_32