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Musical Instrument Identification using LSF and K-means

In this paper, we address the problem of automatically recognising and identifying an instrument from a set of solo recordings. A system using the LSF as features whose statistical properties are learnt using the k-means algorithm is described. During the training phase, models are built by determining an optimised codebook of LSF vectors for each class of instruments. During the identification phase, one codebook is similarly extracted from the unknown audio sample. A distortion measure between two codebooks is then used to retrieve the identity of the presented excerpt. System performances are evaluated using a database of 11 instruments.

Authors: Chetry, Nicolas; Davies, Mike; Sandler, Mark
Affiliation: Queen Mary University
AES Convention:118 (May 2005) Paper Number:6413 Import into BibTeX
Subject:Analysis and Synthesis of Sound

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