Comparison of Two Classification Methods for Musical Instrument Identification

被引：0

作者：

Takahashi, Yuta ^{[1
]}

Kondo, Kazuhiro ^{[1
]}

机构：

[1] Yamagata Univ, Grad Sch Sci & Engn, Yamagata, Japan

来源：

2014 IEEE 3RD GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE) | 2014年

关键词：

Classification; Linear Discriminant Analysis; Random Forest; music information retrieval;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：67 / 68

页数：2