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We present a modular framework for articulatory animation synthesis using speech motion capture data obtained with electromagnetic articulography (EMA). Adapting a skeletal animation approach, the articulatory motion data is applied to a three-dimensional (3D) model of the vocal tract, creating a portable resource that can be integrated in an audiovisual (AV) speech synthesis platform to provide realistic animation of the tongue and teeth for a virtual character. The framework also provides an interface to articulatory animation synthesis, as well as an example application to illustrate its use with a 3D game engine. We rely on cross-platform, open-source software and open standards to provide a lightweight, accessible, and portable workflow.
The importance of modeling speech articulation for high-quality audiovisual (AV) speech synthesis is widely acknowledged. Nevertheless, while state-of-the-art, data-driven approaches to facial animation can make use of sophisticated motion capture te
Text-to-speech and co-speech gesture synthesis have until now been treated as separate areas by two different research communities, and applications merely stack the two technologies using a simple system-level pipeline. This can lead to modeling ine
The development of pathological speech systems is currently hindered by the lack of a standardised objective evaluation framework. In this work, (1) we utilise existing detection and analysis techniques to propose a general framework for the consiste
Electromagnetic articulography (EMA) captures the position and orientation of a number of markers, attached to the articulators, during speech. As such, it performs the same function for speech that conventional motion capture does for full-body move
We contribute MobileVisFixer, a new method to make visualizations more mobile-friendly. Although mobile devices have become the primary means of accessing information on the web, many existing visualizations are not optimized for small screens and ca