This paper examines the use of a number of auditory features in
identifying musical instruments. The Temporal Envelope, Centroid, Melfrequency
Cepstral Coefficients (MFCCs), Inharmonicity, Spectral Irregularity
and Number of Spectral Peaks are all examined. By using these features to train
a Multi-Layered Perceptron (MLP), it is determined that the MFCCs are the
most efficient of these features in musical instrument identification. The
Inharmonicity, Spectral Irregularity and Number of Spectral Peaks offered no
benefit to the classifier. Of the instruments studied, the piano was most
accurately classified and the violin was the least accurately classified
instrument