Despite tremendous progress in natural language processing using deep
learning techniques in recent years, sign language production and comprehension
has advanced very little. One critical barrier is the lack of largescale
datasets available to the public due to the unbearable cost of labeled data
generation. Efforts to provide public data for American Sign Language (ASL)
comprehension have yielded two datasets, comprising more than thousand video
clips. These datasets are large enough to enable a meaningful start to deep
learning research on sign languages but are far too small to lead to any
solution that can be practically deployed. So far, there is still no suitable
dataset for ASL production. We proposed a system that can generate large scale
ASL datasets for continuous ASL. It is suitable for general ASL processing and
is particularly useful for ASL production. The continuous ASL dataset contains
English labeled human articulations in condensed body pose data formats. To
better serve the research community, we are releasing the first version of our
ASL dataset, which contains 30k sentences, 416k words, a vocabulary of 18k
words, in a total of 104 hours. This is the largest continuous sign language
dataset published to date in terms of video duration. We also describe a system
that can evolve and expand the dataset to incorporate better data processing
techniques and more contents when available. It is our hope that the release of
this ASL dataset and the sustainable dataset generation system to the public
will propel better deep-learning research in ASL natural language processing.

提出了一种连续手语数据集生成系统，在发布了包含 30k 个句子、416k 个单词、总计 104 小时的 18k 单词词汇量的最大连续手语数据集时，该系统有助于总体 ASL 处理和特别有助于 ASL 生成。