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 …

Automatic translation from signed to spoken languages is an interdisciplinary research
domain on the intersection of computer vision, machine translation (MT), and linguistics …

Sign languages are based on four components hand shape, place of articulation, hand
orientation, and movement. This paper presents a novel combination of vision based …

The recognition of sign language is a challenging task with an important role in society to
facilitate the communication of deaf persons. We propose a new approach of Spatial …

We propose in this paper a framework for recognizing the sign language alphabet. To
separate hand images from complex backgrounds, we use skin colour and texture attributes …

This works aims to design a statistical machine translation from English text to American
Sign Language (ASL). The system is based on Moses tool with some modifications and the …

Sign language recognition is an important area of human computer interaction (HCI). The
last decade witnessed a good number of publications in this field. Furthermore, several …

In this paper, we propose a block-based histogram of optical flow (BHOF) to generate hand
representation in sign language recognition. Optical flow of the sign language video is …

Sign Language, which is a fully visual language with its own grammar, differs largely from
that of spoken languages [21]. After nearly 30 years of research, SL recognition still in its …

Present work deals with the incorporation of non-manual cues in automatic sign language
recognition. More specifically eye gaze, head pose and facial expressions are discussed in …