Skip to Main content Skip to Navigation
Conference papers

Efficient musical instrument recognition on solo performance music using basic features

Abstract : Musical instrument recognition has gained growing concern for the promise it holds towards advances in musical content description. The present study pursues the goal of showing the efficiency of some basic features for such a recognition task in the realistic situation where solo musical phrases are played. A large and varied database of sounds assembled from different commercial recordings is used to ensure better training and testing conditions, in terms of statistical efficiency. It is found that when combining cepstral features with others describing the audio signal spectral shape, a high recognition accuracy can be achieved in association with Support Vector Machine classification when using a Radial Basis Function kernel.
Document type :
Conference papers
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download

https://hal.telecom-paris.fr/hal-02946911
Contributor : Slim Essid Connect in order to contact the contributor
Submitted on : Wednesday, September 23, 2020 - 3:12:16 PM
Last modification on : Tuesday, October 19, 2021 - 11:16:30 AM
Long-term archiving on: : Thursday, December 3, 2020 - 4:09:04 PM

File

SE_AES-04.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02946911, version 1

Collections

Citation

Slim Essid, Gael Richard, Bertrand David. Efficient musical instrument recognition on solo performance music using basic features. AES 25th conference, Jun 2004, London, United Kingdom. ⟨hal-02946911⟩

Share

Metrics

Record views

36

Files downloads

26