Comparison of two classification methods for Musical Instrument identification

Abstract

In this paper, we compared the Linear Discriminant Analysis (LDA) with Random Forest (RF) for musical instrument identification from clips with a mixture of instruments. As the first step, monotone samples from the Musical Instrument Samples (Univ. Iowa) and RWC Music Database were used to identify the individual instruments. For the Iowa monotones, an overall instrument recognition rate of 24.8% and 82.1% was obtained using LDA and RF, respectively. However, the rate degrades to 54.9% on the RWC monotones even with RF, most likely due to insufficient number of features to cover the increase in variability of this large database.