Evolutionary Spectral Envelope Morphing by Spectral Shape Descriptors

There has been a great collective effort in the search for perceptually meaningful sound transformation techniques. The transformation of sounds matching target sound descriptors is a promising candidate because the descriptors are thought to capture timbral dimensions corresponding to relevant perceptual features. However, matching the descriptors alone is not enough because there are a large number of perceptually different sounds with the same values of descriptors. In this work, we use evolutionary computation to search for the spectral envelope variation that best matches the target spectral shape descriptors. We were able to achieve a more independent control of the descriptors while preserving the overall perceptual features.