• DocumentCode
    3529942
  • Title

    Registration of multimodal data for estimating the parameters of an articulatory model

  • Author

    Aron, M. ; Toutios, A. ; Berger, M.-O. ; Kerrien, E. ; Wrobel-Dautcourt, B. ; Laprie, Y.

  • Author_Institution
    LORIA/ CNRS/ INRIA Nancy Grand-Est, Villers les Nancy
  • fYear
    2009
  • fDate
    19-24 April 2009
  • Firstpage
    4489
  • Lastpage
    4492
  • Abstract
    Being able to animate a speech production model with articulatory data would open applications in many domains. In this paper, we first consider the problem of acquiring articulatory data from non invasive image and sensor modalities: dynamic ultrasound (US) images, stereovision 3D data, electromagnetic sensors and MRI. We here especially focus on automatic registration methods which enable the fusion of the articulatory features in a common frame. We then derive articulatory parameters by fitting these features with Maeda´s model. To our knowledge, it is the first attempt to derive articulatory parameters from features automatically extracted and registered between the modalities. Results prove the soundness of the approach and the reliability of the fused articulatory data.
  • Keywords
    computer animation; feature extraction; speech processing; MRI; Maeda model; animation; articulatory data; articulatory model; articulatory parameter; automatic registration; dynamic ultrasound image; electromagnetic sensor; feature extraction; multimodal data registration; noninvasive image; parameter estimation; sensor modality; speech production; stereovision 3D data; Animation; Data mining; Head; Image sensors; Magnetic resonance imaging; Parameter estimation; Sensor systems; Speech; Tongue; Ultrasonic imaging; multimodal registration; speech analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-2353-8
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2009.4960627
  • Filename
    4960627