Open Access

Musical Instrument Timbres Classification with Spectral Features

EURASIP Journal on Advances in Signal Processing20032003:943279

DOI: 10.1155/S1110865703210118

Received: 10 May 2002

Published: 30 January 2003

Abstract

A set of features is evaluated for recognition of musical instruments out of monophonic musical signals. Aiming to achieve a compact representation, the adopted features regard only spectral characteristics of sound and are limited in number. On top of these descriptors, various classification methods are implemented and tested. Over a dataset of 1007 tones from 27 musical instruments, support vector machines and quadratic discriminant analysis show comparable results with success rates close to 70% of successful classifications. Canonical discriminant analysis never had momentous results, while nearest neighbours performed on average among the employed classifiers. Strings have been the most misclassified instrument family, while very satisfactory results have been obtained with brass and woodwinds. The most relevant features are demonstrated to be the inharmonicity, the spectral centroid, and the energy contained in the first partial.

Keywords

timbre classification content-based audio indexing/searching pattern recognition audio features extraction

Authors’ Affiliations

(1)
Dipartimento di Scienze dell'Informazione, Università degli Studi di Milano

Copyright

© Copyright © 2003 Hindawi Publishing Corporation 2003