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 visual languages, with vocabularies as rich as their spoken language
counterparts. However, current deep-learning based Sign Language Production (SLP) …

Signed languages are the primary means of communication for many deaf and hard of
hearing individuals. Since signed languages exhibit all the fundamental linguistic properties …

State-of-the-art techniques common to low resource Machine Translation (MT) are applied to
improve MT of spoken language text to Sign Language (SL) glosses. In our experiments, we …

Recently, sign language researchers have turned to sign language interpreted TV
broadcasts, comprising (i) a video of continuous signing and (ii) subtitles corresponding to …

Sign Language Production (SLP) aims to generate the visual appearance of sign language
according to the spoken language, in which a key procedure is to translate sign Gloss to …

Despite recent successes with neural models for sign language translation (SLT), translation
quality still lags behind spoken languages because of the data scarcity and modality gap …

Automatic sign language processing is gaining popularity in Natural Language Processing
(NLP) research (Yin et al., 2021). In machine translation (MT) in particular, sign language …

Neural Sign Language Production (SLP) aims to automatically translate from spoken
language sentences to sign language videos. Historically the SLP task has been broken into …