Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/85242
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dc.contributor.authorChu, Ba Thanh-
dc.contributor.authorTrinh, Van Loan-
dc.contributor.authorDao, Thi Le Thuy-
dc.date.accessioned2023-02-07T09:02:17Z-
dc.date.available2023-02-07T09:02:17Z-
dc.date.issued2022-
dc.identifier.issn1813-9663-
dc.identifier.urihttps://dspace.ctu.edu.vn/jspui/handle/123456789/85242-
dc.description.abstractWe 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.vi_VN
dc.language.isoenvi_VN
dc.relation.ispartofseriesJournal of Computer Science and Cybernetics;Vol.38, No.01 .- P.63-83-
dc.subjectIdentificationvi_VN
dc.subjectClassificationvi_VN
dc.subjectFolk songsvi_VN
dc.subjectVietnamesevi_VN
dc.subjectCheovi_VN
dc.subjectQuanhovi_VN
dc.subjectCNNvi_VN
dc.subjectLSTMvi_VN
dc.subjectCRNNvi_VN
dc.titleAutomatic identification of some Vietnamese folk songs Cheo and Quanho using deep neural networksvi_VN
dc.typeArticlevi_VN
Appears in Collections:Tin học và Điều khiển học (Journal of Computer Science and Cybernetics)

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