Representing timbre dynamics of a musical instrument: comparison between GA and PCA

The time-varying spectral characteristics of clarinet sounds were used to build maps with the purpose of representing the great variety of sounds a musical instrument may produce. A database of notes performed in several intensities and covering all the extension of the clarinet was used. This work compares two kinds of orthogonal bases used to create a sound map from time-varying curves of sound partials. The first mapping was derived by principal component analysis and the second was created using multiple wavetable synthesis (MWS) and genetic algorithms. These bases defined spectral sub-spaces capable of representing and grouping all tested sounds, which were validated by auditory tests. Sub-spaces involving larger groups of notes were used to compare the sounds according to the distance metrics of the representation