Interpolation of tongue fleshpoint kinematics from combined EMA position and orientation data

Andrew J. Kolb, Michael T. Johnson, Jeffrey Berry

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

Articulatory data such as that collected via electromagnetic articulography (EMA) are valuable for many speech applications, including speech modeling, recognition, and synthesis. Nearly all current EMA applications and methods focus on the use of positional sensor data, even though modern 3D-EMA systems also capture sensor orientation, which provides significant additional information about articulator posture and vocal tract shape. To address this problem, this paper introduces a new method for interpolating untracked tongue fleshpoint positions from the combined position and orientation data of three EMA sensors on the tongue, using additional reference sensors for evaluating interpolation error. Comparison of interpolated and measured data illustrated effectiveness of the new method in providing additional tongue shape and position features. The results suggest that analytic methods that combine sensor position and orientation data are able to improve the characterization of tongue kinematics even using a small number of EMA sensors.

Original languageEnglish
Pages (from-to)2177-2181
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2015-January
StatePublished - 2015
Event16th Annual Conference of the International Speech Communication Association, INTERSPEECH 2015 - Dresden, Germany
Duration: Sep 6 2015Sep 10 2015

Bibliographical note

Publisher Copyright:
Copyright © 2015 ISCA.

Keywords

  • EMA
  • Quaternions

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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