Automatic glottal segmentation using local-based active contours and application to glottovibrography

Authors:
Sevasti-Zoi Karakozoglou;Nathalie Henrich;Christophe d'Alessandro;Yannis Stylianou
Affiliations:
LIMSI-CNRS, Orsay Cedex, France and Computer Science Department, University of Crete, Heraklion, Greece and Computer Science Department, University Paris-Sud 11, Orsay Cedex, France;Department of Speech and Cognition, GIPSA-lab, UMR 5216: CNRS, INPG, University Stendhal, UJF, Grenoble, France;LIMSI-CNRS, Orsay Cedex, France;Computer Science Department, University of Crete, Heraklion, Greece
Venue:
Speech Communication
Year:
2012

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Abstract

The use of high-speed videoendoscopy (HSV) for the assessment of vocal-fold vibrations dictates the development of efficient techniques for glottal image segmentation. We present a new glottal segmentation method using a local-based active contour framework. The use of local-based features and the exploitation of the vibratory pattern allows for dealing effectively with image noise and cases where the glottal area consists of multiple regions. A scheme for precise glottis localization is introduced, which facilitates the segmentation procedure. The method has been tested on a database of 60 HSV recordings. Comparisons with manual verification resulted in less than 1% difference on the average glottal area. These errors mainly come from detection failure in the posterior or anterior parts of the glottal area. Comparisons with automatic threshold-based glottal detection point out the necessity of complete frameworks for automatic detection. The glottovibrogram (GVG), a representation of glottal vibration is also presented. This easily readable representation depicts the time-varying distance of the vocal-fold edges.