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The movement of tongue plays an important role in pronunciation. Visualizing the movement of tongue can improve speech intelligibility and also helps learning a second language. However, hardly any research has been investigated for this topic. In this paper, a framework to synthesize continuous ultrasound tongue movement video from speech is presented. Two different mapping methods are introduced as the most important parts of the framework. The objective evaluation and subjective opinions show that the Gaussian

The observation of frequency folding in graph spectrum during down-sampling for signals on bipartite graphs—analogous to the same phenomenon in Fourier domain for regularly sampled signals—has led to the development of critically sampled wavelet filterbanks such as GraphBior. However, typical graph-signals live on general graphs that are not necessarily bipartite.

Given a set of training shapes and an input image with a shape similar to some of the elements in the training set, this poster introduces a new implicit kernel sparse model with a twofold goal. First, to obtain an implicit kernel sparse neighbor based combination that best represents the object. Second, to accurately segment the object taking into accounts both the high-level implicit kernel presentation and the low-level image information.

By exploiting the geometry information, the estimation performance (efficiency, accuracy and robustness) can be improved, and the conventional searching procedure can also be avoided. The concept of the methods can be used in the parameters estimation field, especially .