Encoder-decoder CNN models for automatic tracking of tongue contours in real-time ultrasound data
MH Mozaffari, WS Lee - Methods, 2020 - Elsevier
One application of medical ultrasound imaging is to visualize and characterize human
tongue shape and motion in real-time to study healthy or impaired speech production. Due …
tongue shape and motion in real-time to study healthy or impaired speech production. Due …
[HTML][HTML] Domain adaptation for ultrasound tongue contour extraction using transfer learning: A deep learning approach
M Hamed Mozaffari, WS Lee - The Journal of the Acoustical Society of …, 2019 - pubs.aip.org
Automatic and precise delineating of the tongue surface in real-time frames is a challenging
task because of the noisy nature of ultrasound images and rapid changes of the tongue …
task because of the noisy nature of ultrasound images and rapid changes of the tongue …
Automated tongue contour extraction from ultrasound sequences using signal enhancing neural network and energy minimized spline
Ultrasonography is widely used in linguistic study, speech therapy, language training, and
impaired speech production. Real-time visualization of the shape, contour, and motion of the …
impaired speech production. Real-time visualization of the shape, contour, and motion of the …
wUnet: A new network used for ultrasonic tongue contour extraction
G Li, J Chen, Y Liu, J Wei - Speech Communication, 2022 - Elsevier
Ultrasound imaging is becoming a practical tool in silent speech recognition. It is a
challenge to accurately extract tongue contours due to the soft tissue characteristics of the …
challenge to accurately extract tongue contours due to the soft tissue characteristics of the …
US2Mask: Image-to-mask generation learning via a conditional GAN for cardiac ultrasound image segmentation
Cardiac ultrasound (US) image segmentation is vital for evaluating clinical indices, but it
often demands a large dataset and expert annotations, resulting in high costs for deep …
often demands a large dataset and expert annotations, resulting in high costs for deep …
Deep learning for automatic tracking of tongue surface in real-time ultrasound videos, Landmarks instead of Contours
MH Mozaffari, N Yamane… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
One usage of medical ultrasound imaging is to visualize and characterize human tongue
shape and motion during a real-time speech to study healthy or impaired speech production …
shape and motion during a real-time speech to study healthy or impaired speech production …
Pronunciation and technology
Research and teaching of second language pronunciation increasingly is intertwined with
the use of technology, both for analysis and description and for pronunciation learning …
the use of technology, both for analysis and description and for pronunciation learning …
Irisnet: Deep learning for automatic and real-time tongue contour tracking in ultrasound video data using peripheral vision
The progress of deep convolutional neural networks has been successfully exploited in
various real-time computer vision tasks such as image classification and segmentation …
various real-time computer vision tasks such as image classification and segmentation …
Bownet: Dilated convolution neural network for ultrasound tongue contour extraction
MH Mozaffari, WS Lee - arXiv preprint arXiv:1906.04232, 2019 - arxiv.org
Ultrasound imaging is safe, relatively affordable, and capable of real-time performance. One
application of this technology is to visualize and to characterize human tongue shape and …
application of this technology is to visualize and to characterize human tongue shape and …
Second language pronunciation training by ultrasound-enhanced visual augmented reality
MH Mozaffari, WS Lee - 2021 IEEE International Conference on …, 2021 - ieeexplore.ieee.org
Evaluation of ultrasound-enhanced pronunciation training methods has shown that
visualizing articulator's system as biofeedback to language learners will significantly …
visualizing articulator's system as biofeedback to language learners will significantly …