In this paper we present a revised and improved version of a recently proposed extended source-filter model for sound synthesis, transformation and hybridization of harmonic instruments. This extension focuses mainly on the application for impulsively excited instruments like piano or guitar, but also improves synthesis results for continuously driven instruments including their hybrids. This technique comprises an extensive analysis of an instruments sound database, followed by the estimation of a generalized instrument model reflecting timbre variations according to selected control parameters. Such an instrument model allows for natural sounding transformations and expressive control of instrument sounds regarding its control parameters.

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Sound textures are often noisy and chaotic. The processing of these sounds must be based on the statistics of its corresponding time-frequency representation. In order to transform sound textures with existing mechanisms, a statistical model based on the STFT representation is favored. In this article, the relation between statistics of a sound texture and its time-frequency representation is explored. We proposed an algorithm to extract and modify the statistical properties of a sound texture based on its STFT representation. It allows us to extract the statistical model of a sound texture and resynthesise the sound texture after modifications have been made. It could also be used to generate new samples of the sound texture from a given sample. The results of the experiment show that the algorithm is capable of generating high quality sounds from an extracted model. This result could serve as a basis for transformations like morphing or high-level control of sound textures.

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