Open AccessMusic Genre Classifier using Machine Learning Algorithms
Author(s) -
Sparsh Nagpal
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.35381
Subject(s) - computer science , categorization , music information retrieval , musical , artificial intelligence , classifier (uml) , ranging , machine learning , speech recognition , art , telecommunications , visual arts
Audio data extraction and analysis is important and less explored compared to other forms of data. Here we use an Audio dataset (GTZan) to extract musical information and categorize the musical genre based on the parameters of audio. We compared the study on seven Machine learning algorithms and tested on unvisited user data to see the model performance seeing the algorithms’ accuracy ranging from 45% to 87%.