Segmentation of tongue shapes during vowel production in magnetic resonance images based on statistical modelling

Abstract

Quantification of the anatomic and functional aspects of the tongue is pertinent to analyse the mechanisms involved in speech production. Speech requires dynamic and complex articulation of the vocal tract organs, and the tongue is one of the main articulators during speech production.Magnetic Resonance (MR) imaging has been widely used in speech related studies. Moreover, the segmentation of such images of speech organs is required to extract reliable statistical data.However, standards solutions to analyse a large set of articulatory images have not yet been established. Therefore, this article presents an approach to segment the tongue in 2D MR images and statistically model the segmented tongue shapes. The proposed approach assesses the articulator morphology based on an Active Shape Model, which captures the shape variability of the tongue during speech production. To validate this new approach, a dataset of mid-sagittal MR images acquired from four subjects was used, and key aspects of the shape of the tongue during the vocal production of relevant European Portuguese (EP) vowels were evaluated.

A survey of artificial intelligence in tongue image for disease diagnosis and syndrome differentiation

“…Using medical ultrasound image to visualize and characterize human tongue shape and motion in real-time would do a great favor to study healthy or impaired speech production; thus, some tongue contour segmentation methods 70 – 72 of ultrasound image in real time have been proposed by the team of Hamed Mozaffari; furthermore, they 73 have used the augmented reality of ultrasound data from the extracted tongue movement to provide a real-time visual feedback to improve the training trend of language learners. There are also some researchers 74 who used magnetic resonance signals of tongue images to perform tongue segmentation.…”