4 accepted papers
Sign languages convey information through multiple channels. The handshape channel is an important manual component for conveying the message. In the literature, it is mainly modeled as a sequence of images of discrete postures even in the case of dynamic gestures, leading to blurring problems in de…
Sign language is vital for communication within the deaf and hard-of-hearing community. Avatar-based methods and deep learning techniques like Generative Adversarial Networks have shown promise in generating sign language video content. One of the challenges in sign language generation is the evalua…
Sign language recognition involves modeling of multichannel information such as, hand shapes, hand movements. This requires also sufficient sign language specific data. This is a challenge as sign languages are inherently under-resourced. In the literature, it has been shown that hand shape informat…
Sign language conveys information through multiple channels, such as hand shape, hand movement, and mouthing. Modeling this multichannel information is a highly challenging problem. In this paper, we elucidate the link between spoken language and sign language in terms of production phenomenon and p…