Browsing by Subject "International Speech Communication Association"
Now showing items 1-4 of 4
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End-to-end convolutional sequence learning for ASL fingerspelling recognition
(2019)Although fingerspelling is an often overlooked component of sign languages, it has great practical value in the communication of important context words that lack dedicated signs. In this paper we consider the problem of ... -
MobilipNet: Resource-efficient deep learning based lipreading
(2019)Recent works in visual speech recognition utilize deep learning advances to improve accuracy. Focus however has been primarily on recognition performance, while ignoring the computational burden of deep architectures. In ... -
Multimodal sign language recognition via temporal deformable convolutional sequence learning
(2020)In this paper we address the challenging problem of sign language recognition (SLR) from videos, introducing an end-to-end deep learning approach that relies on the fusion of a number of spatio-temporal feature streams, ... -
Resource-adaptive deep learning for visual speech recognition
(2020)We focus on the problem of efficient architectures for lipreading that allow trading-off computational resources for visual speech recognition accuracy. In particular, we make two contributions: First, we introduce ...