Wavetable matching is the process of finding the parameters needed to resynthesize a musical instrument tone using wavetable synthesis. The most important parameters to find are the wavetable basis spectra. Previous work on wavetable matching has used a genetic algorithm (GA) to select the basis spectra. However, such work has assumed the original tone was harmonic or nearly harmonic. This assumption is not satisfied by tones such as those from the plucked strings. In this thesis, we introduce an adaptive wavetable matching technique for pitched inharmonic tones. It employs a hierarchical grouping method to group the partials with similar normalized frequency deviations. The GA is then applied to individual groups to find their basis spectra. No prior knowledge about the inharmonicity o...[ Read more ]

Wavetable matching is the process of finding the parameters needed to resynthesize a musical instrument tone using wavetable synthesis. The most important parameters to find are the wavetable basis spectra. Previous work on wavetable matching has used a genetic algorithm (GA) to select the basis spectra. However, such work has assumed the original tone was harmonic or nearly harmonic. This assumption is not satisfied by tones such as those from the plucked strings. In this thesis, we introduce an adaptive wavetable matching technique for pitched inharmonic tones. It employs a hierarchical grouping method to group the partials with similar normalized frequency deviations. The GA is then applied to individual groups to find their basis spectra. No prior knowledge about the inharmonicity of tone is required. Results show that for 18 instrument tones with varying amounts of inharmonicity, the new method improves the perceived match on pitched inharmonic tones compared to ordinary wavetable matching with less memory and resynthesis computation than additive synthesis.