  Sign Language Recognition is a challenging research domain. It has recently
seen several advancements with the increased availability of data. In this
paper, we introduce the BosphorusSign22k, a publicly available large scale sign
language dataset aimed at computer vision, video recognition and deep learning
research communities. The primary objective of this dataset is to serve as a
new benchmark in Turkish Sign Language Recognition for its vast lexicon, the
high number of repetitions by native signers, high recording quality, and the
unique syntactic properties of the signs it encompasses. We also provide
state-of-the-art human pose estimates to encourage other tasks such as Sign
Language Production. We survey other publicly available datasets and expand on
how BosphorusSign22k can contribute to future research that is being made
possible through the widespread availability of similar Sign Language
resources. We have conducted extensive experiments and present baseline results
to underpin future research on our dataset.
