Excitation signature extraction for pitched musical instrument timbre analysis using Higher Order Statistics

The timber of pitched musical instruments is analyzed through the excitation signature by means of Higher Order Statistics (HOS) and subspace analysis. To describe the features of instrument sounding mechanism, the excitation signature is proposed, which decisively characterizes the musical instrument category rather than the difference within one kind of instrument family. Subspace analysis is applied to get more efficient timbre representations for musical instrument classification. Experimental results show that HOS based features provide more significant timbre patterns in both time and frequency domain in comparison with the 2^nd order statistics features. Dimensional reduction of excitation signature is also considered for the efficiency of musical instrument classification.