Measurement of Tongue Tip Velocity from Real-Time MRI and Phase-Contrast Cine-MRI in Consonant Production

Abstract

We evaluate velocity of the tongue tip with magnetic resonance imaging (MRI) using two independent approaches. The first one consists in acquisition with a real-time technique in the mid-sagittal plane. Tracking of the tongue tip manually and with a computer vision method allows its trajectory to be found and the velocity to be calculated as the derivative of the coordinate. We also propose to use another approach—phase contrast MRI—which enables velocities of the moving tissues to be measured directly. We recorded the sound simultaneously with the MR acquisition which enabled us to make conclusions regarding the relation between the movements and the sound. We acquired the data from two French-speaking subjects articulating /tata/. The results of both methods are in qualitative agreement and are consistent with other reviewer techniques used for evaluation of the tongue tip velocity.

Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers

“…In this work we report on a multi-modal MRI database consisting of 2D real-time and 3D static MR images of the vocal tract of 10 French speakers. The protocol used for the real-time MRI acquisitions for our dataset was successfully used by multiple groups in the context of the study of the articulators’ motion 30 – 33 . While performing investigations on the vocal tract organs, it is crucial to consider the diversity of their movements during speech production.…”

Realistic Dynamic Numerical Phantom for MRI of the Upper Vocal Tract

“…This type of acquisition should be preferred for the clinical assessment of speech where a speech and language therapist usually interacts with the The ability to image dynamically the upper vocal tract using a non-invasive modality such as Magnetic Resonance Imaging (MRI) allows one to gain an understanding of the dynamic processes of speech and swallowing and this is consequently an active field of research [3,4]. The technique is particularly interesting in the field of linguistics to understand articulations of sounds by both native speakers (e.g., [5][6][7][8][9]) and learning in non-native learners (e.g., [10,11]) but also to study singing [12][13][14] and air-instrument music players [15,16].…”

A segmentation-informed deep learning framework to register dynamic two-dimensional magnetic resonance images of the vocal tract during speech

“…Dynamic magnetic resonance imaging (MRI) has several advantages over other dynamic imaging techniques: it is non-invasive, can image planes of any orientation and does not use ionising radiation. These advantages have resulted in its increasing use to visualise the articulators during speech [1] , [2] , [3] , [4] , [5] , [6] , [10] , [11] , [12] , [13] . Dynamic MRI is also beginning to be used in the clinical assessment of speech, for example the speech of patients with velopharyngeal insufficiency [14] , [15] , [16] , [17] , [18] , [19] , patients following glossectomy [20] , [21] and people who stutter [22] .…”

“…Several studies have used traditional deformable registration methods to estimate displacement fields between images in series of dynamic 2D MR images of the vocal tract during speech [11] , [12] , [13] . In [11] , [12] the diffeomorphic demons method [28] was used to estimate displacement fields, while in [13] a registration method based on optical flow [53] was used. In [12] , [13] , images showing the tongue and soft palate in contact were registered to images showing the tongue and soft palate not in contact.…”

“…In [11] , [12] the diffeomorphic demons method [28] was used to estimate displacement fields, while in [13] a registration method based on optical flow [53] was used. In [12] , [13] , images showing the tongue and soft palate in contact were registered to images showing the tongue and soft palate not in contact. However, neither study evaluated nor discussed if the registration methods captured this change in contact.…”