4 papers
HATL: Hierarchical Adaptive-Transfer Learning Framework for Sign Language Machine Translation
Nada Shahin, Leila Ismail
Sign Language Machine Translation (SLMT) aims to bridge communication between Deaf and hearing individuals. However, its progress is constrained by scarce datasets, limited signer…
ADAT: Time-Series-Aware Adaptive Transformer Architecture for Sign Language Translation
Nada Shahin, Leila Ismail
Current sign language machine translation systems rely on recognizing hand movements, facial expressions and body postures, and natural language processing, to convert signs into t…
GLoT: A Novel Gated-Logarithmic Transformer for Efficient Sign Language Translation
Nada Shahin, Leila Ismail
Machine Translation has played a critical role in reducing language barriers, but its adaptation for Sign Language Machine Translation (SLMT) has been less explored. Existing works…
From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation Systems: Survey, Taxonomy and Performance Evaluation
Nada Shahin, Leila Ismail
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, signs…