Including Signed Languages in Natural Language Processing

kayo yin, Amit Moryossef, Julie Hochgesang3, Yoav Goldberg, Malihe Alikhani

Abstract:

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 of natural language, we believe that tools
and theories of Natural Language Processing
(NLP) are crucial towards its modeling. However, existing research in Sign Language Processing (SLP) seldom attempt to explore and
leverage the linguistic organization of signed
languages. This position paper calls on the
NLP community to include signed languages
as a research area with high social and scientific impact. We first discuss the linguistic
properties of signed languages to consider during their modeling. Then, we review the limitations of current SLP models and identify the
open challenges to extend NLP to signed languages. Finally, we urge (1) the adoption of
an efficient tokenization method; (2) the development of linguistically-informed models; (3)
the collection of real-world signed language
data; (4) the inclusion of local signed language
communities as an active and leading voice in
the direction of research.