Music genre classification and music recommendation by using deep learning

Today, music is a very important and perhaps inseparable part of people's daily life. There are many genres of music and these genres are different from each other, resulting in people to have different preferences of music. As a result, it is an important and up-to-date issue to classify music...

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Vydané v:Electronics letters Ročník 56; číslo 12; s. 627 - 629
Hlavní autori: Elbir, A, Aydin, N
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: The Institution of Engineering and Technology 11.06.2020
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ISSN:0013-5194, 1350-911X, 1350-911X
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Popis
Shrnutí:Today, music is a very important and perhaps inseparable part of people's daily life. There are many genres of music and these genres are different from each other, resulting in people to have different preferences of music. As a result, it is an important and up-to-date issue to classify music and to recommend people new music in music listening applications and platforms. Classifying music by their genre is one of the most useful techniques used to solve this problem. There are a number of approaches for music classification and recommendation. One approach is based on the acoustic characteristics of music. In this study, a music genre classification system and music recommendation engine, which focuses on extracting representative features that have been obtained by a novel deep neural network model, have been proposed. Acoustic features extracted from these networks have been utilised for music genre classification and music recommendation on a data set.
ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2019.4202