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- W4285367203 abstract "It is difficult to adjust the parameters of a complex synthesizer to create the desired sound. As such, sound matching, the estimation of synthesis parameters that can replicate a certain sound, is a task that has often been researched, utilizing optimization methods such as genetic algorithm (GA). In this paper, we introduce a novelty-based objective for GA-based sound matching. Our contribution is two-fold. First, we show that the novelty objective is able to improve the quality of sound matching by maintaining phenotypic diversity in the population. Second, we introduce a quality diversity approach to the problem of sound matching, aiming to find a diverse set of matching sounds. We show that the novelty objective is effective in producing high-performing solutions that are diverse in terms of specified audio features. This approach allows for a new way of discovering sounds and exploring the capabilities of a synthesizer." @default.
- W4285367203 created "2022-07-14" @default.
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- W4285367203 date "2021-09-08" @default.
- W4285367203 modified "2023-10-18" @default.
- W4285367203 title "Quality Diversity for Synthesizer Sound Matching" @default.
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- W4285367203 doi "https://doi.org/10.23919/dafx51585.2021.9768271" @default.
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