A real-time framework for visual feedback of articulatory data using   statistical shape models
  We present a novel open-source framework for visualizing electromagnetic articulography (EMA) data in real-time, with a modular framework and anatomically accurate tongue and palate models derived by multilinear subspace learning. 
Kristy James (DFKI), Alexander Hewer (DFKI), Ingmar Steiner (DFKI),   Stefanie Wuhrer (MORPHEO)
cs.HC