Real-time sign language translation systems are of paramount importance in enabling
communication for deaf and hard-of-hearing individuals. This population relies on various …

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

Most sign language translation (SLT) methods to date require the use of gloss annotations to
provide additional supervision information, however, the acquisition of gloss is not easy. To …

Sign languages are visual languages which convey information by signers' handshape,
facial expression, body movement, and so forth. Due to the inherent restriction of …

Hand gesture serves as a crucial role during the expression of sign language. Current deep
learning based methods for sign language understanding (SLU) are prone to over-fitting due …

Most of the research to date focuses on bilingual sign language translation (BSLT).
However, such models are inefficient in building multilingual sign language translation …

With the growing Deaf and Hard of Hearing population worldwide and the persistent
shortage of certified sign language interpreters, there is a pressing need for an efficient …

Direct speech-to-speech translation (S2ST) with discrete units leverages recent progress in
speech representation learning. Specifically, a sequence of discrete representations derived …

Sign Language Production (SLP) aims to convert text or audio sentences into sign language
videos corresponding to their semantics, which is challenging due to the diversity and …

Speech Recognition builds a bridge between the multimedia streaming (audio-only, visual-
only or audio-visual) and the corresponding text transcription. However, when training the …