Segmentation and 3D reconstruction of the vocal tract from MR images - a comparative study

Abstract

Speech production is an important human function involving a set of organs with specific morphological and dynamic aspects. The inter-speaker variability, the coarticulation or the nasality are some interesting aspects to improve a realistic 3D modeling of the vocal tract. For this, the understanding of the mechanism of speech production is crucial, as the current image data is not sufficient to reproduce truthfully the speakers anatomy and articulation. Hence, the goal of 3D modeling is to generate the complete geometrical and dynamical information concerning the vocal tract from medical images, such as from magnetic reso-nance imaging (MRI). This work aims to describe and compare two different segmentation techniques to at-tain the 3D shape of the vocal tract during speech production from MR images: the former based on manual tracing of the vocal tract contours and the latter based on image thresholding. Thus, the segmented cross-sectional areas were measured, and 3D models were built from the sagittal data by blending the contours ob-tained from the two segmentation techniques. The mean error of the measures computed were low for both segmentation techniques, which let us conclude that the techniques are useful to evaluate the vocal tract ge-ometry accurately. Additionally, the 3D models built using both segmentation techniques were also very similar and truthful. However, when the coronal data was used, various difficulties occurred.