A real-time framework for visual feedback of articulatory data using statistical shape models
arXiv:1612.06114
Abstract
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.
17th Annual Conference of the International Speech Communication Association (Interspeech), Oct 2016, San Francisco, United States