Music Genre Classification with Machine Learning
Pavan P, Manoj K S, Shivakumar K R, Shruthi P
GTZAN, MFCC features, K nearest neighbor, Spectrogram, wav format.
Tune performs a significant position in absolutely everyone’s life. Music genre type approach is based totally on Mel Frequency Cepstral coefficients (MFCC). The Mel-Frequency Cepstrum (MFC) encrypt the strength spectrum of an audio. MFCC are premeditated as the discrete Fourier transform (DCT) of the logarithm of the wave spectrum. Spectrogram is used to correlate the collection of all of Mel Frequency Cepstral Coefficient’s. A spectrogram refers to the frequency information of a tune. It depicts the depth of frequencies on y axis and detailed time intervals on x axis. Darker coloration in spectrogram shows the more potent frequencies. A genre of the song categorizes the tune based on the frequency. Okay Nearest Neighbor (KNN) set of rules is used for prediction. The approach comprising of all capabilities, improves the accuracy for predicting the style of music.
Article Details
Unique Paper ID: 155461

Publication Volume & Issue: Volume 9, Issue 1

Page(s): 922 - 926
Article Preview & Download

Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on

Social Media

Google Verified Reviews