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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.

πŸš€ Conference Pioneer β€” INTERSPEECH 2016
🧭 Keyword Pioneer β€” articulatory datum
🐝 Cross-Pollinator β€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio

Authors

Kristy James , Alexander Hewer , Ingmar Steiner , Stefanie Wuhrer

Topics

Machine Learning > Core Methods > Representation Learning

Keywords

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