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- W2769505100 abstract "These days, digital music storage systems (DMSS) in Vietnam usually arrange pieces of music according to the composer’s name and the song’s title, whereas listeners need to search for songs based on genres and contents. This increases the demand for categorizing songs in accordance with genres in DMSS, which enables listeners to search for the most wanted music. However, with a large number of songs collected, the way to classify them for easy management becomes a challenge for all DMSS. Therefore, it is necessary to build up an automatic sorting system. This paper suggests a new method of extracting specific timbral disposition including timbral texture, rhythmic content by using wavelet convert. Thanks to such distinctive features, KNN and SVM methods are utilized to identify types of music files. This study is conducted on four types of music: Bolero, Cai luong (reformed theatre), Cheo (classical theatre) and Hat Boi (traditional opera). The findings show that the reliability is up to 93.75% and 94% corresponding to KNN and SVM on the timbral texture. Moreover, these suggested methods are simple, effective, speedy, and suitable for Vienamese music sorting systems today." @default.
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- W2769505100 date "2017-01-01" @default.
- W2769505100 modified "2023-09-25" @default.
- W2769505100 title "Phân loại nhạc Việt Nam theo thể loại dựa trên âm sắc và nhịp điệu" @default.
- W2769505100 doi "https://doi.org/10.22144/ctu.jsi.2017.020" @default.
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