ISCA Archive Interspeech 2014
ISCA Archive Interspeech 2014

Reconstruction of mistracked articulatory trajectories

Qiang Fang, Jianguo Wei, Fang Hu

Kinematic articulatory data are important for researches of speech production, articulatory speech synthesis, robust speech recognition, and speech inversion. Electromagnetic Articulograph (EMA) is a widely used instrument for collecting kinematic articulatory data. However, in EMA experiment, one or more coils attached to articulators are possible to be mistracked due to various reasons. To make full use of the EMA data, we attempt to reconstruct the location of mistracked coils with Gaussian Mixture Model (GMM) regression method. In this paper, we explore how additional information (spectrum, articulatory velocity, etc.) affects the performance of the proposed method. The result indicates that acoustic feature (MFCC) is the most effective additional features that improve the reconstruction performance.

doi: 10.21437/Interspeech.2014-194

Cite as: Fang, Q., Wei, J., Hu, F. (2014) Reconstruction of mistracked articulatory trajectories. Proc. Interspeech 2014, 2342-2345, doi: 10.21437/Interspeech.2014-194

  author={Qiang Fang and Jianguo Wei and Fang Hu},
  title={{Reconstruction of mistracked articulatory trajectories}},
  booktitle={Proc. Interspeech 2014},