Musical instrument identification using principal component analysis and multi-layered perceptrons

被引：3

作者：

Loughran, Rosin ^{[1
]}

Walker, Jacqueline ^{[1
]}

O'Neill, Michael

O'Farrell, Marion ^{[1
]}

机构：

[1] Univ Limerick, Limerick, Ireland

来源：

2008 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING, VOLS 1 AND 2, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/ICALIP.2008.4590236

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This study aims to create an automatic musical instrument classifier by extracting audio features from real sample sounds. These features are reduced using Principal Component Analysis and the resultant data is used to train a Multi-Layered Perceptron. We found that the RMS temporal envelope and the evolution of the centroid gave the most interesting results of the features studied These results were found to be competitive whether the scope of the data was across one octave or across the range of each instrument.

引用

页码：643 / 648

页数：6

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