Translation of Sign Language Glosses to Text Using Sequence-to-Sequence Attention Models
Nikolaos Arvanitis, Constantinos Constantinopoulos, Dimitrios Kosmopoulos · 2019
This work deals with the problem of Sign Language Translation and more specifically with translating Glosses to text. We applied Sequence to Sequence models with attention mechanism to a parallel gloss to English corpus. This is the first work that used these models to translate American gloss sentences to English. We present our experiments on several network architectures with three different attention functions. The results are very promising and can be useful for the further implementation of a full sign language recognition system.