Sign language plays a crucial role as a distinct and vital mode of communication for diverse
groups of people in society. Each sign language encompasses a wide array of signs, each …

Sign language is commonly used by deaf or speech impaired people to communicate but
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …

In this paper we present a system for word-level sign language recognition based on the
Transformer model. We aim at a solution with low computational cost, since we see great …

Audio-visual speech recognition (AVSR) is one of the most promising solutions for reliable
speech recognition, particularly when audio is corrupted by noise. Additional visual …

Signed languages are visual languages produced by the movement of the hands, face, and
body. In this paper, we evaluate representations based on skeleton poses, as these are …

Abstract Isolated Sign Language Recognition (ISLR) fits nicely in the domain of problems
that can be handled by graph-structured spatial-temporal algorithms. A recent multiscale …

Automatic sign language recognition lies at the intersection of natural language processing
(NLP) and computer vision. The highly successful transformer architectures, based on multi …

Sign language recognition (SLR) enables the deaf and speech-impaired community to
integrate and communicate effectively with the rest of society. Word level or isolated SLR is a …

Sign language recognition using computational models is a challenging problem that
requires simultaneous spatio-temporal modeling of the multiple sources, ie faces, hands …

Sign language is commonly used by deaf or mute people to communicate but requires
extensive effort to master. It is usually performed with the fast yet delicate movement of hand …