Skip to main content
  • Research Article
  • Published:

Musical Instrument Timbres Classification with Spectral Features


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.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Giulio Agostini.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Agostini, G., Longari, M. & Pollastri, E. Musical Instrument Timbres Classification with Spectral Features. EURASIP J. Adv. Signal Process. 2003, 943279 (2003).

Download citation

  • Received:

  • Revised:

  • Published:

  • DOI: