Music genre classification using On-line Dictionary Learning

Mettu, Srinivas and Roy, D and C, Krishna Mohan (2015) Music genre classification using On-line Dictionary Learning. In: International Joint Conference on Neural Networks, IJCNN 2014, 6-11 July, 2014, Beijing; China.

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Abstract

In this paper, an approach for music genre classification based on sparse representation using MARSYAS features is proposed. The MARSYAS feature descriptor consisting of timbral texture, pitch and beat related features is used for the classification of music genre. On-line Dictionary Learning (ODL) is used to achieve sparse representation of the features for developing dictionaries for each musical genre. We demonstrate the efficacy of the proposed framework on the Latin Music Database (LMD) consisting of over 3000 tracks spanning 10 genres namely Axé, Bachata, Bolero, Forró, Gaúcha, Merengue, Pagode, Salsa, Sertaneja and Tango.

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IITH Creators:	IITH Creators ORCiD C, Krishna Mohan UNSPECIFIED
Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Dictionary Learning; Music Genre Classification; Sparse Representation
Subjects:	Computer science > Computer programming, programs, data Computer science > Big Data Analytics
Divisions:	Department of Computer Science & Engineering
Depositing User:	Team Library
Date Deposited:	18 Nov 2014 09:12
Last Modified:	01 Sep 2017 09:20
URI:	http://raiithold.iith.ac.in/id/eprint/855
Publisher URL:	https://doi.org/10.1109/IJCNN.2014.6889516
Related URLs:	Google Scholar

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