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2016 Interspeech INTERSPEECH 2016

A Real-Time Framework for Visual Feedback of Articulatory Data Using Statistical Shape Models

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.

🚀 Conference Pioneer - Interspeech 2016

Authors

Kristy James, Alexander Hewer, Ingmar Steiner, Stefanie Wuhrer

Topics

Machine Learning > Core Methods > Representation Learning

Keywords

statistical shape model electromagnetic articulography articulatory data real-time visualization multilinear subspace learning
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