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https://dspace.ctu.edu.vn/jspui/handle/123456789/85242
Title: | Automatic identification of some Vietnamese folk songs Cheo and Quanho using deep neural networks |
Authors: | Chu, Ba Thanh Trinh, Van Loan Dao, Thi Le Thuy |
Keywords: | Identification Classification Folk songs Vietnamese Cheo Quanho CNN LSTM CRNN |
Issue Date: | 2022 |
Series/Report no.: | Journal of Computer Science and Cybernetics;Vol.38, No.01 .- P.63-83 |
Abstract: | We can say that music in general is an indispensable spiritual food in human life. For Vietnamese people, folk music plays a very important role, it has entered the minds of every Vietnamese person right from the moment of birth through lullabies for children. In Vietnam, there are many different types of folk songs that everyone loves, and each has many different tunes. In order to archive and search music works with a very large quantity, including folk songs, it is necessary to automatically classify and identify those works. This paper presents the method of determining the feature parameters and then using the Convolution Neural Network (CNN), Long-Short Term Memory networks (LSTM), and Convolutional Recurrent Neural Network (CRNN) to classify and identify some Vietnamese folk tunes as Quanho and Cheo. Our experimental results show that the average highest classification and identification accuracy are 99.92% and 97.67%, respectively. |
URI: | https://dspace.ctu.edu.vn/jspui/handle/123456789/85242 |
ISSN: | 1813-9663 |
Appears in Collections: | Tin học và Điều khiển học (Journal of Computer Science and Cybernetics) |
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