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E. Benetos, C. Kotropoulos, T. Lidy, A. Rauber:
"Testing supervised classifiers based on non-negative matrix factorization to musical instrument classification";
Poster: EUSIPCO European Signal Processing Conference, Florence, Italy; 2006-09-04 - 2006-09-08; in: "Proceeedings of the 14th European Signal Processing Conference", (2006).

In this paper, a class of algorithms for automatic classification
of individual musical instrument sounds is presented. Two feature
sets were employed, the first containing perceptual features and
MPEG-7 descriptors and the second containing rhythm patterns
developed for the SOMeJB project. The features were measured for
300 sound recordings consisting of 6 different musical instrument
classes. Subsets of the feature set are selected using
branch-and-bound search, obtaining the most suitable features for
classification. A class of supervised classifiers is developed
based on the non-negative matrix factorization (NMF). The standard
NMF method is examined as well as its modifications: the local and
the sparse NMF. The experiments compare the two feature sets
alongside the various NMF algorithms. The results demonstrate an
almost perfect classification for the first set using the standard
NMF algorithm (classification error 1.0 %), outperforming the
state-of-the-art techniques tested for the aforementioned
experiment.

http://publik.tuwien.ac.at/files/pub-inf_3607.pdf