Spatiotemporal-atlas-based dynamic speech imaging

M, Fu; Woo, Jonghye; Liang, Zhi Pei; Sutton, Bradley P.

doi:10.1117/12.2216528

Cited by 4 publications

(5 citation statements)

References 29 publications

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“…Further shortening of acquisition time may result from better a priori models and advanced regularization. 23 To determine the reconstruction parameters, we made several simulations to explore the effects of rank L, regularization parameter 𝜆, penalization term L 1 -norm, L 2 -norm, Huber penalty, and fraction of data being used. To choose a proper rank, we need to assure an adequate number of temporal bases to cover the speech articulatory dynamics.…”

Section: Discussionmentioning

confidence: 99%

“…Further shortening of acquisition time may result from better a priori models and advanced regularization. 23 …”

Section: Discussionmentioning

confidence: 99%

“…We have seen some success with this approach in children with our previous method, although the current proposed shorter overall acquisition time is still likely necessary to achieve high success with children subjects. Further shortening of acquisition time may result from better a priori models and advanced regularization 23 …”

Section: Discussionmentioning

confidence: 99%

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Enhancing linguistic research through 2‐mm isotropic 3D dynamic speech MRI optimized by sparse temporal sampling and low‐rank reconstruction

Jin

Shosted

Xing

et al. 2022

Magnetic Resonance in Med

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Purpose To enable a more comprehensive view of articulations during speech through near‐isotropic 3D dynamic MRI with high spatiotemporal resolution and large vocal‐tract coverage. Methods Using partial separability model‐based low‐rank reconstruction coupled with a sparse acquisition of both spatial and temporal models, we are able to achieve near‐isotropic resolution 3D imaging with a high frame rate. The total acquisition time of the speech acquisition is shortened by introducing a sparse temporal sampling that interleaves one temporal navigator with four randomized phase and slice‐encoded imaging samples. Memory and computation time are improved through compressing coils based on the region of interest for low‐rank constrained reconstruction with an edge‐preserving spatial penalty. Results The proposed method has been evaluated through experiments on several speech samples, including a standard reading passage. A near‐isotropic 1.875 × 1.875 × 2 mm3 spatial resolution, 64‐mm through‐plane coverage, and a 35.6‐fps temporal resolution are achieved. Investigations and analysis on specific speech samples support novel insights into nonsymmetric tongue movement, velum raising, and coarticulation events with adequate visualization of rapid articulatory movements. Conclusion Three‐dimensional dynamic images of the vocal tract structures during speech with high spatiotemporal resolution and axial coverage is capable of enhancing linguistic research, enabling visualization of soft tissue motions that are not possible with other modalities.

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Section: Discussionmentioning

confidence: 99%

“…Further shortening of acquisition time may result from better a priori models and advanced regularization. 23 …”

Section: Discussionmentioning

confidence: 99%

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Enhancing linguistic research through 2‐mm isotropic 3D dynamic speech MRI optimized by sparse temporal sampling and low‐rank reconstruction

Jin

Shosted

Xing

et al. 2022

Magnetic Resonance in Med

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“…One can tackle this problem using either motion quantities derived from tagged-MRI such as strain and the mean of the magnitude of the motion field as in Eq. (11) or motion quantities derived from cine-MRI [10,33]. These quantities can serve as a motion descriptor to find temporal correspondences across subjects.…”

Section: Time Alignment Of Speech Movements Across Subjectsmentioning

confidence: 99%

Speech Map: a statistical multimodal atlas of 4D tongue motion during speech from tagged and cine MR images

Woo

Xing

Stone

et al. 2017

Computer Methods in Biomechanics and Biomedical Engineering: Im

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Quantitative measurement of functional and anatomical traits of 4D tongue motion in the course of speech or other lingual behaviors remains a major challenge in scientific research and clinical applications. Here, we introduce a statistical multimodal atlas of 4D tongue motion using healthy subjects, which enables a combined quantitative characterization of tongue motion in a reference anatomical configuration. This atlas framework, termed Speech Map, combines cine- and tagged-MRI in order to provide both the anatomic reference and motion information during speech. Our approach involves a series of steps including (1) construction of a common reference anatomical configuration from cine-MRI, (2) motion estimation from tagged-MRI, (3) transformation of the motion estimations to the reference anatomical configuration, and (4) computation of motion quantities such as Lagrangian strain. Using this framework, the anatomic configuration of the tongue appears motionless, while the motion fields and associated strain measurements change over the time course of speech. In addition, to form a succinct representation of the high-dimensional and complex motion fields, principal component analysis is carried out to characterize the central tendencies and variations of motion fields of our speech tasks. Our proposed method provides a platform to quantitatively and objectively explain the differences and variability of tongue motion by illuminating internal motion and strain that have so far been intractable. The findings are used to understand how tongue function for speech is limited by abnormal internal motion and strain in glossectomy patients.

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“…The second aspect corresponds to rapid geometrical changes and, consequently, changes in the area function, which have a strong acoustic impact [18,19]. In the same conditions, atlas techniques could also improve speech imaging techniques [20] as it would allow low-quality images to be captured at a very high frame rate and the acquired image resolution to be increased by registering a high-resolution atlas to them. Indeed, spatio-temporal atlases are usually based on cine MRI to capture the 3D geometry of the vocal tract and its temporal evolution [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

3D Dynamic Spatiotemporal Atlas of the Vocal Tract during Consonant–Vowel Production from 2D Real Time MRI

et al. 2022

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In this work, we address the problem of creating a 3D dynamic atlas of the vocal tract that captures the dynamics of the articulators in all three dimensions in order to create a global speaker model independent of speaker-specific characteristics. The core steps of the proposed method are the temporal alignment of the real-time MR images acquired in several sagittal planes and their combination with adaptive kernel regression. As a preprocessing step, a reference space was created to be used in order to remove anatomical information of the speakers and keep only the variability in speech production for the construction of the atlas. The adaptive kernel regression makes the choice of atlas time points independently of the time points of the frames that are used as an input for the construction. The evaluation of this atlas construction method was made by mapping two new speakers to the atlas and by checking how similar the resulting mapped images are. The use of the atlas helps in reducing subject variability. The results show that the use of the proposed atlas can capture the dynamic behavior of the articulators and is able to generalize the speech production process by creating a universal-speaker reference space.

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Spatiotemporal-atlas-based dynamic speech imaging

Cited by 4 publications

References 29 publications

Enhancing linguistic research through 2‐mm isotropic 3D dynamic speech MRI optimized by sparse temporal sampling and low‐rank reconstruction

Enhancing linguistic research through 2‐mm isotropic 3D dynamic speech MRI optimized by sparse temporal sampling and low‐rank reconstruction

Speech Map: a statistical multimodal atlas of 4D tongue motion during speech from tagged and cine MR images

3D Dynamic Spatiotemporal Atlas of the Vocal Tract during Consonant–Vowel Production from 2D Real Time MRI

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