Adding Dynamic Smoothing to Mixture Mosaicing Synthesis

TitleAdding Dynamic Smoothing to Mixture Mosaicing Synthesis
Publication TypeConference Paper
Year of Publication2011
Conference NameSpars11: Workshop on Signal Processing with Adaptive Sparse Structured Representations
AuthorsColeman, G., Bonada J., & Maestre E.
Conference Start Date27/06/2011
Conference LocationEdinburgh, Scotland, UK
Keywordsbasis pursuit denoising, kalman filter, mosaicing
Recent works in sound mosaicing synthesis [1], [2] have
proposed algorithms that permit instantaneous mixtures of several
sources atoms, based on sparse signal representation techniques. We
propose combining l1 regularization with linear dynamical smoothing
as in the Kalman filter (also in [3], [4]) to promote desired transitions
between atoms, while adapting the generic approach to the mixture
mosaicing context. Furthermore, we modify the dynamics cost slightly
to further promote sparse scores in the case of non-negativity. This is a
work in progress in which we can present some sound examples, but for
which the proposal is not fully validated.
Full Documentfiles/publications/dynmos_spars11.pdf