UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 4
April-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2104053


Registration ID:
307336

Page Number

378-382

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Title

Music Genre Classification Using Convolutional Neural Network (CNN)

Abstract

Music genres are categorical labels designed to differentiate the various pieces of music. Until recently, such classification was done manually, but now automatic music genre classifications can assist or replace human users in this process and contribute to a valuable framework in music information retrieval systems. Our designed system works on the above idea to extract features from audio files and learn from them to classify them across genres using a Convolutional Neural Network (CNN), all done on commodity hardware.

Key Words

Music Genre, Classification, Machine Learning, Genre, Convolutional Neural Network

Cite This Article

"Music Genre Classification Using Convolutional Neural Network (CNN)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.378-382, April-2021, Available :http://www.jetir.org/papers/JETIR2104053.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Music Genre Classification Using Convolutional Neural Network (CNN)", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp378-382, April-2021, Available at : http://www.jetir.org/papers/JETIR2104053.pdf

Publication Details

Published Paper ID: JETIR2104053
Registration ID: 307336
Published In: Volume 8 | Issue 4 | Year April-2021
DOI (Digital Object Identifier):
Page No: 378-382
Country: Mumbai, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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