Abstract
Articulatory Synthesis consists in reproducing speech by means of models of the vocal tract and of articulatory processes. Recent advances in Magnetic Resonance Imaging (MRI) allowed for important improvements with respect to the speech comprehension and the forms taken by the vocal tract. However, one of the main challenges in the field is the fast and at the same time high-quality acquisition of image sequences. Since adopting more powerful acquisition devices might be financially inviable, we propose a method for the spatio-temporal resolution enhancement of the obtained sequences using only digital image processing techniques. The approach involves two stages: (1) the temporal resolution enhancement by means of a motion compensated interpolation technique; and (2) the spatial resolution enhancement by means of a super resolution image reconstruction technique. Considering the spatial resolution enhancement, inspired by two methods available in the literature, three adaptations of the Wiener filter were proposed: the statistical interpolation, the multi-temporal approach, and the adaptive Wiener filter. In all cases, a separable Markovian model and an isotropic model were compared for the characterization of the spatial correlation structures. Considering all Wiener filter-based approaches, the adaptive Wiener filter outperformed all other approaches.
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