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* Corresponding author 1 MMCI - Cluster of Excellence -Multimodal Computing and Interaction- 2 DFKI - German Research Center for Artificial Intelligence 3 Allgemeine Linguistik - Allgemeine Linguistik Computational Linguistics and phonetics 4 CSTR - The Centre for Speech Technology Research Edinburgh 5 PAROLE - Analysis, perception and recognition of speech Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery

Abstract : 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 movements acquired with optical modalities, a long-time staple technique of the animation industry. In this paper, EMA data is processed from a motion-capture perspective and applied to the visualization of an existing multimodal corpus of articulatory data, creating a kinematic 3D model of the tongue and teeth by adapting a conventional motion capture based animation paradigm. This is accomplished using off-the-shelf, open-source software. Such an animated model can then be easily integrated into multimedia applications as a digital asset, allowing the analysis of speech production in an intuitive and accessible manner. The processing of the EMA data, its co-registration with 3D data from vocal tract magnetic resonance imaging MRI and dental scans, and the modeling workflow are presented in detail, and several issues discussed.

Keywords : speech production articulatory data electromagnetic articulography vocal tract motion capture visualization





Author: Ingmar Steiner - Korin Richmond - Slim Ouni -

Source: https://hal.archives-ouvertes.fr/



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