DOIONLINE 
DOIONLINE Publish In |
International Journal of Management and Applied Science (IJMAS)-IJMAS |
 Journal Home Volume Issue |
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Issue |
Volume-8,Issue-8 ( Aug, 2022 ) | |||||||||
Paper Title |
A Study of Web-Based Bangla Music Genre Classification using Machine Learning Approach | |||||||||
Author Name |
Abdul Hady Akash, K.B.M. Tahmiduzzaman, Md. Thoufiq Zumma, Tanmoy Mondal, Mohammad Sakib Shahriar, Tanha Ahmed Nijhum | |||||||||
Affilition |
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Pages |
75-79 | |||||||||
Abstract |
Abstract - It's crucial to categorize music by genre if you want to propose music and understand its specifics. English music classification requires a lot of work. Use several machine learning techniques, such as K-NN, NN, and SVM, to categorize music. Bangladesh has a thriving music scene. It also features the clothes unique to that culture. There hasn't been any significant attempt to categorize Bangla music using machine learning, though. It is crucial to estimate the amount of Bengali songs. There are several songs that are well-liked by native speakers, numbering in the millions. There are a number of articles on Bengali music categorization that focus on the melody of the song rather than text-based lyrics. Bengali music may be categorized into a wide range of genres since it has so many different sorts and styles. Consider "Bangla Adhunik," "Bangla Baul," "Bangla Band," and "Nazrul Geety" for beginners. For each genre, we utilize 50 audio songs (.wav files). extracted various items properties of audio signals in the time and frequency domains from digital audio files (such as MP3 files). Keywords - KNN, MFCC, Machine Learning, Bangla Music, Adhunik, Baul, Band Music, and Nazrulgeeti | |||||||||
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