Open AccessGenre of Bangla Music: A Machine Classification Learning Approach
Author(s) -
Abhijit Bhowmik,
Azm Ehtesham Chowdhury
Publication year - 2019
Publication title -
the aiub journal of science and engineering
Language(s) - English
Resource type - Journals
eISSN - 2520-4890
pISSN - 1608-3679
DOI - 10.53799/ajse.v18i2.42
Subject(s) - bengali , computer science , search engine indexing , scheme (mathematics) , variety (cybernetics) , set (abstract data type) , artificial intelligence , natural language processing , feature (linguistics) , feature extraction , musical , machine learning , linguistics , mathematical analysis , philosophy , mathematics , programming language , art , visual arts
The necessity for designing autonomous indexing tools to establish expressive and efficient means of describing musical media content is well recognized. Music genre classification systems are significant to manage and use music databases. This research paper proposes an enhanced method to automatically classify music into different genre using a machine learning approach and presents the insight and results of the application of the proposed scheme to the classification of a large set of The Bangla music content, a South-East Asian language rich with a variety of music genres developed over many centuries. Building upon musical feature extraction and decision-making techniques, we propose new features and procedures to achieve enhanced accuracy. We demonstrate the efficacy of the proposed method by extracting features from a dataset of hundreds of The Bangla music pieces and testing the automatic classification decisions. This is the first development of an automated classification technique applied specifically to the Bangla music to the best of our knowledge, while the superior accuracy of the method makes it universally applicable.