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

SDW-ASL: A Dynamic System to Generate Large Scale Dataset for Continuous American Sign Language