Sebastian J. Schlecht is a postdoctoral researcher at the International Audio Laboratories of the Friedrich-Alexander-University Erlangen-Nuremberg, Germany. His research interests include spatial audio processing with an emphasis on artificial reverberation, localization, panning, and 6-degrees-of-freedom virtual and mixed reality applications. In particular, his research efforts have been directed towards the intersection of mathematical filter design, efficient algorithms, perceptual aspects, and sound design. Sebastian Schlecht complements his scientific work with being an avid musician, and a research and development consultant at the Fraunhofer Institute for Integrated Circuits (IIS) in Erlangen.
PhD in Acoustic Signal Processing, 2017
University of Erlangen-Nuremberg, Germany
M.Sc. in Digital Music Processing, 2011
Queen Mary, University of London, UK
M.Sc. in Applied Mathematics, 2010
University of Trier, Germany
This paper proposes a method to optimize the decorrelation properties of a sparse noise sequence, called velvet noise, to generate short sparse FIR decorrelation filters.
This is a collection of posts which aims at reproducing plots and data from papers.
A central topic in the design of spatial FDNs is the choice of the feedback matrix that governs the interaction between spatially distributed elements and therefore the spatial impression.