The automatic identification of musical instruments is a relatively unexplored and potentially very important field for its promise to free humans from time-consuming searches on the Internet and indexing of audio material. Speaker identification techniques have been used in this paper to determine the properties (features) which are most effective in identifying a statistically significant number of sounds representing four classes of musical instruments (oboe, sax, clarinet, flute) excerpted from actual performances. Features examined include cepstral coefficients, constant-Q coefficients, spectral centroid, autocorrelation coefficients, and moments of the time wave. The number of these coefficients was varied, and in the case of cepstral coefficients, ten coefficients were sufficient for identification. [...]
展开▼
