Name
Title | ||
|---|---|---|
Excitation signature extraction for pitched musical instrument timbre analysis using Higher Order Statistics |
Abstract | ||
|---|---|---|
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 2nd order statistics features. Dimensional reduction of excitation signature is also considered for the efficiency of musical instrument classification. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICME.2010.5582571 | ICME |
Keywords | Field | DocType |
excitation signature,hos,signal processing,timbre,statistics,subspace analysis,dimensional reduction,2nd order statistics features,excitation signature extraction,pitched musical instrument timbre analysis,higher order statistics,musical instruments,musical instrument classification,order statistic,feature extraction,covariance matrix,harmonic analysis,principal component analysis,frequency domain | Frequency domain,Subspace topology,Pattern recognition,Computer science,Higher-order statistics,Musical instrument classification,Feature extraction,Musical instrument,Speech recognition,Artificial intelligence,Dimensional reduction,Timbre | Conference |
ISSN | ISBN | Citations |
1945-7871 | 978-1-4244-7491-2 | 1 |
PageRank | References | Authors |
0.37 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruolun Liu | 1 | 1 | 0.37 |
| Udo Zölzer | 2 | 27 | 12.39 |
| Mijail Guulemard | 3 | 1 | 0.37 |