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Title: Vocal Tract Articulatory Contour Detection in Real-Time Magnetic Resonance Images Using Spatio-Temporal Context
Authors: Hebbar S.A.
Sharma R.
Somandepalli K.
Toutios A.
Narayanan S.
Issue Date: 2020
Citation: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings , Vol. 2020-May , , p. 7354 - 7358
Abstract: Due to its ability to visualize and measure the dynamics of vocal tract shaping during speech production, real-time magnetic resonance imaging (rtMRI) has emerged as one of the prominent research tools. The ability to track different articulators such as the tongue, lips, velum, and the pharynx is a crucial step toward automating further scientific and clinical analysis. Recently, various researchers have addressed the problem of detecting articulatory boundaries, but those are primarily limited to static-image based methods. In this work, we propose to use information from temporal dynamics together with the spatial structure to detect the articulatory boundaries in rtMRI videos. We train a convolutional LSTM network to detect and label the articulatory contours. We compare the produced contours against reference labels generated by iteratively fitting a manually created subject-specific template. We observe that the proposed method outperforms solely image-based methods, especially for the difficult-to-track articulators involved in airway constriction formation during speech. © 2020 IEEE.
Appears in Collections:2. Conference Papers

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