Abstract
Automatic classification of musical instruments is a challenging task. Music data classification has become a very popular research in the digital world. Classification of the musical instruments required a huge manual process. This system classifies the musical instruments from a several acoustic features that includes MFCC, Sonogram and MFCC combined with Sonogram. SVM and kNN are two modeling techniques used to classify the features. In this paper, to simply musical instruments classifications based on its features which are extracted from various instruments using recent algorithms. The proposed work compares the performance of kNN with SVM. Identifying the musical instruments and computing its accuracy is performed with the help of SVM and kNN classifier, using the combination of MFCC and Sonogram with SVM a high accuracy rate of 98% achieve in classifying musical instruments. The system tested sixteen musical instruments to find out the accuracy level using SVM and kNN
Publisher
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Subject
Electrical and Electronic Engineering,Mechanics of Materials,Civil and Structural Engineering,General Computer Science
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献