Using Statistical Deformable Models to Reconstruct Vocal Tract Shape from Magnetic Resonance Images

Abstract

The mechanisms involved in speech production are complex and have thus been subject to growing attention by the scientific community. Magnetic Resonance Imaging (MRI) has been proven to be a powerful means in the understanding of the morphology of the vocal tract. Over the last few years, statistical deformable models have been successfully used to identify and characterize bones and organs in medical images and Point Distribution Models (PDMs) have gained particular relevance. In this work, we have studied the suitability of these models to characterize and further reconstruct the shape of the vocal tract in the articulation of Portuguese European (EP) speech sounds, one of the most spoken languages worldwide, with the aid of MR images. Therefore, a PDM has been built from a set of MR images acquired during the artificially sustained articulation of 25 EP speech sounds. Following this, the capacity of this statistical model to characterize the shape deformation of the vocal tract during the production of sounds was analyzed. Next, the model was used to reconstruct 5 EP oral vowels and the EP fricative consonants. As far as a study on speech production is concerned, this study is considered to be the first approach to characterize and reconstruct the vocal tract shape from MR images by using PDMS. In addition, the findings achieved permit one to conclude that this modelling technique compels an enhanced understanding of the dynamic speech events involved in sustained articulations based on MRI, which are of particular interest for speech rehabilitation and simulation.