This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

Abstract Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to
communicate on a daily basis. However, the communication with hearing people still faces …

Abstract Prior work on Sign Language Translation has shown that having a mid-level sign
gloss representation (effectively recognizing the individual signs) improves the translation …

Despite existing pioneering works on sign language translation (SLT), there is a non-trivial
obstacle, ie, the limited quantity of parallel sign-text data. To tackle this parallel data …

One of the factors that have hindered progress in the areas of sign language recognition,
translation, and production is the absence of large annotated datasets. Towards this end, we …

Sign language recognition is a challenging problem where signs are identified by
simultaneous local and global articulations of multiple sources, ie hand shape and …

In this paper, a comparative experimental assessment of computer vision-based methods for
sign language recognition is conducted. By implementing the most recent deep neural …

Abstract Vision-based Continuous Sign Language Recognition (CSLR) aims to recognize
unsegmented signs from image streams. Overfitting is one of the most critical problems in …

Sign languages use multiple asynchronous information channels (articulators), not just the
hands but also the face and body, which computational approaches often ignore. In this …

Despite the recent success of deep learning in video-related tasks, deep models typically
focus on the most discriminative features, ignoring other potentially non-trivial and …