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

Content Provider	IEEE Xplore Digital Library
Author	Aron, M. Toutios, A. Berger, M.-O. Kerrien, E. Wrobel-Dautcourt, B. Laprie, Y.
Copyright Year	2009
Description	Author affiliation: LORIA/ CNRS/ INRIA Nancy Grand-Est, BP 101, 54602 Villers les Nancy, France (Aron, M.; Toutios, A.; Berger, M.-O.; Kerrien, E.; Wrobel-Dautcourt, B.; Laprie, Y.)
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.
Starting Page	4489
Ending Page	4492
File Size	424750
Page Count	4
File Format	PDF
ISBN	9781424423538
ISSN	15206149
DOI	10.1109/ICASSP.2009.4960627
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-04-19
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parameter estimation Magnetic resonance imaging Tongue Ultrasonic imaging Data mining Image sensors Animation Sensor systems Head Speech multimodal registration speech analysis
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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