This paper addresses the usefulness of the segmentation of musical sounds into transient/non-transient parts for the task of machine recognition of musical instruments. We put into light the discriminative power of the attack-transient segments on the basis of objective criteria, consistent with the well-known psychoacoustics findings. Moreover, we show that, paradoxically, it is not always optimal to consider such a segmentation of the audio in a machine recognition system given decision length constraints. Our evaluation exploits efficient automatic segmentation techniques, a wide variety of signal processing features as well as feature selection algorithms and Support Vector Machine classification. The sound database used is composed of real-world mono-instrument phrases.

Authors: Daudet, Laurent; David, Bertrand; EssidSSID, Slim; Leveau, Pierre; Richard, Gael
Affiliations: ENST; Laboratoire d'Acoustique Musicale(See document for exact affiliation information.)
AES Convention: 118 (May 2005) Paper Number: 6415
Publication Date: May 1, 2005 Import into BibTeX
Subject: Analysis and Synthesis of Sound
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=13131

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